Case Study vs. Research

What's the difference.

Case study and research are both methods used in academic and professional settings to gather information and gain insights. However, they differ in their approach and purpose. A case study is an in-depth analysis of a specific individual, group, or situation, aiming to understand the unique characteristics and dynamics involved. It often involves qualitative data collection methods such as interviews, observations, and document analysis. On the other hand, research is a systematic investigation conducted to generate new knowledge or validate existing theories. It typically involves a larger sample size and employs quantitative data collection methods such as surveys, experiments, or statistical analysis. While case studies provide detailed and context-specific information, research aims to generalize findings to a broader population.

Further Detail

Introduction.

When it comes to conducting studies and gathering information, researchers have various methods at their disposal. Two commonly used approaches are case study and research. While both methods aim to explore and understand a particular subject, they differ in their approach, scope, and the type of data they collect. In this article, we will delve into the attributes of case study and research, highlighting their similarities and differences.

A case study is an in-depth analysis of a specific individual, group, event, or phenomenon. It involves a detailed examination of a particular case to gain insights into its unique characteristics, context, and dynamics. Case studies often employ multiple sources of data, such as interviews, observations, and documents, to provide a comprehensive understanding of the subject under investigation.

One of the key attributes of a case study is its focus on a specific case, which allows researchers to explore complex and nuanced aspects of the subject. By examining a single case in detail, researchers can uncover rich and detailed information that may not be possible with broader research methods. Case studies are particularly useful when studying rare or unique phenomena, as they provide an opportunity to deeply analyze and understand them.

Furthermore, case studies often employ qualitative research methods, emphasizing the collection of non-numerical data. This qualitative approach allows researchers to capture the subjective experiences, perspectives, and motivations of the individuals or groups involved in the case. By using open-ended interviews and observations, researchers can gather rich and detailed data that provides a holistic view of the subject.

However, it is important to note that case studies have limitations. Due to their focus on a specific case, the findings may not be easily generalized to a larger population or context. The small sample size and unique characteristics of the case may limit the generalizability of the results. Additionally, the subjective nature of qualitative data collection in case studies may introduce bias or interpretation challenges.

Research, on the other hand, is a systematic investigation aimed at discovering new knowledge or validating existing theories. It involves the collection, analysis, and interpretation of data to answer research questions or test hypotheses. Research can be conducted using various methods, including surveys, experiments, and statistical analysis, depending on the nature of the study.

One of the primary attributes of research is its emphasis on generating generalizable knowledge. By using representative samples and statistical techniques, researchers aim to draw conclusions that can be applied to a larger population or context. This allows for the identification of patterns, trends, and relationships that can inform theories, policies, or practices.

Research often employs quantitative methods, focusing on the collection of numerical data that can be analyzed using statistical techniques. Surveys, experiments, and statistical analysis allow researchers to measure variables, establish correlations, and test hypotheses. This objective approach provides a level of objectivity and replicability that is crucial for scientific inquiry.

However, research also has its limitations. The focus on generalizability may sometimes sacrifice the depth and richness of understanding that case studies offer. The reliance on quantitative data may overlook important qualitative aspects of the subject, such as individual experiences or contextual factors. Additionally, the controlled nature of research settings may not fully capture the complexity and dynamics of real-world situations.

Similarities

Despite their differences, case studies and research share some common attributes. Both methods aim to gather information and generate knowledge about a particular subject. They require careful planning, data collection, analysis, and interpretation. Both case studies and research contribute to the advancement of knowledge in their respective fields.

Furthermore, both case studies and research can be used in various disciplines, including social sciences, psychology, business, and healthcare. They provide valuable insights and contribute to evidence-based decision-making. Whether it is understanding the impact of a new treatment, exploring consumer behavior, or investigating social phenomena, both case studies and research play a crucial role in expanding our understanding of the world.

In conclusion, case study and research are two distinct yet valuable approaches to studying and understanding a subject. Case studies offer an in-depth analysis of a specific case, providing rich and detailed information that may not be possible with broader research methods. On the other hand, research aims to generate generalizable knowledge by using representative samples and quantitative methods. While case studies emphasize qualitative data collection, research focuses on quantitative analysis. Both methods have their strengths and limitations, and their choice depends on the research objectives, scope, and context. By utilizing the appropriate method, researchers can gain valuable insights and contribute to the advancement of knowledge in their respective fields.

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Case Study | Definition, Examples & Methods

Published on 5 May 2022 by Shona McCombes . Revised on 30 January 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organisation, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating, and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyse the case.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

  • Provide new or unexpected insights into the subject
  • Challenge or complicate existing assumptions and theories
  • Propose practical courses of action to resolve a problem
  • Open up new directions for future research

Unlike quantitative or experimental research, a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

If you find yourself aiming to simultaneously investigate and solve an issue, consider conducting action research . As its name suggests, action research conducts research and takes action at the same time, and is highly iterative and flexible. 

However, you can also choose a more common or representative case to exemplify a particular category, experience, or phenomenon.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

  • Exemplify a theory by showing how it explains the case under investigation
  • Expand on a theory by uncovering new concepts and ideas that need to be incorporated
  • Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews, observations, and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data .

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis, with separate sections or chapters for the methods , results , and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyse its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

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All You Wanted to Know About How to Write a Case Study

is case study different from thesis

What do you study in your college? If you are a psychology, sociology, or anthropology student, we bet you might be familiar with what a case study is. This research method is used to study a certain person, group, or situation. In this guide from our dissertation writing service , you will learn how to write a case study professionally, from researching to citing sources properly. Also, we will explore different types of case studies and show you examples — so that you won’t have any other questions left.

What Is a Case Study?

A case study is a subcategory of research design which investigates problems and offers solutions. Case studies can range from academic research studies to corporate promotional tools trying to sell an idea—their scope is quite vast.

What Is the Difference Between a Research Paper and a Case Study?

While research papers turn the reader’s attention to a certain problem, case studies go even further. Case study guidelines require students to pay attention to details, examining issues closely and in-depth using different research methods. For example, case studies may be used to examine court cases if you study Law, or a patient's health history if you study Medicine. Case studies are also used in Marketing, which are thorough, empirically supported analysis of a good or service's performance. Well-designed case studies can be valuable for prospective customers as they can identify and solve the potential customers pain point.

Case studies involve a lot of storytelling – they usually examine particular cases for a person or a group of people. This method of research is very helpful, as it is very practical and can give a lot of hands-on information. Most commonly, the length of the case study is about 500-900 words, which is much less than the length of an average research paper.

The structure of a case study is very similar to storytelling. It has a protagonist or main character, which in your case is actually a problem you are trying to solve. You can use the system of 3 Acts to make it a compelling story. It should have an introduction, rising action, a climax where transformation occurs, falling action, and a solution.

Here is a rough formula for you to use in your case study:

Problem (Act I): > Solution (Act II) > Result (Act III) > Conclusion.

Types of Case Studies

The purpose of a case study is to provide detailed reports on an event, an institution, a place, future customers, or pretty much anything. There are a few common types of case study, but the type depends on the topic. The following are the most common domains where case studies are needed:

Types of Case Studies

  • Historical case studies are great to learn from. Historical events have a multitude of source info offering different perspectives. There are always modern parallels where these perspectives can be applied, compared, and thoroughly analyzed.
  • Problem-oriented case studies are usually used for solving problems. These are often assigned as theoretical situations where you need to immerse yourself in the situation to examine it. Imagine you’re working for a startup and you’ve just noticed a significant flaw in your product’s design. Before taking it to the senior manager, you want to do a comprehensive study on the issue and provide solutions. On a greater scale, problem-oriented case studies are a vital part of relevant socio-economic discussions.
  • Cumulative case studies collect information and offer comparisons. In business, case studies are often used to tell people about the value of a product.
  • Critical case studies explore the causes and effects of a certain case.
  • Illustrative case studies describe certain events, investigating outcomes and lessons learned.

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Case Study Format

The case study format is typically made up of eight parts:

  • Executive Summary. Explain what you will examine in the case study. Write an overview of the field you’re researching. Make a thesis statement and sum up the results of your observation in a maximum of 2 sentences.
  • Background. Provide background information and the most relevant facts. Isolate the issues.
  • Case Evaluation. Isolate the sections of the study you want to focus on. In it, explain why something is working or is not working.
  • Proposed Solutions. Offer realistic ways to solve what isn’t working or how to improve its current condition. Explain why these solutions work by offering testable evidence.
  • Conclusion. Summarize the main points from the case evaluations and proposed solutions. 6. Recommendations. Talk about the strategy that you should choose. Explain why this choice is the most appropriate.
  • Implementation. Explain how to put the specific strategies into action.
  • References. Provide all the citations.

How to Write a Case Study

Let's discover how to write a case study.

How to Write a Case Study

Setting Up the Research

When writing a case study, remember that research should always come first. Reading many different sources and analyzing other points of view will help you come up with more creative solutions. You can also conduct an actual interview to thoroughly investigate the customer story that you'll need for your case study. Including all of the necessary research, writing a case study may take some time. The research process involves doing the following:

  • Define your objective. Explain the reason why you’re presenting your subject. Figure out where you will feature your case study; whether it is written, on video, shown as an infographic, streamed as a podcast, etc.
  • Determine who will be the right candidate for your case study. Get permission, quotes, and other features that will make your case study effective. Get in touch with your candidate to see if they approve of being part of your work. Study that candidate’s situation and note down what caused it.
  • Identify which various consequences could result from the situation. Follow these guidelines on how to start a case study: surf the net to find some general information you might find useful.
  • Make a list of credible sources and examine them. Seek out important facts and highlight problems. Always write down your ideas and make sure to brainstorm.
  • Focus on several key issues – why they exist, and how they impact your research subject. Think of several unique solutions. Draw from class discussions, readings, and personal experience. When writing a case study, focus on the best solution and explore it in depth. After having all your research in place, writing a case study will be easy. You may first want to check the rubric and criteria of your assignment for the correct case study structure.

Read Also: 'CREDIBLE SOURCES: WHAT ARE THEY?'

Although your instructor might be looking at slightly different criteria, every case study rubric essentially has the same standards. Your professor will want you to exhibit 8 different outcomes:

  • Correctly identify the concepts, theories, and practices in the discipline.
  • Identify the relevant theories and principles associated with the particular study.
  • Evaluate legal and ethical principles and apply them to your decision-making.
  • Recognize the global importance and contribution of your case.
  • Construct a coherent summary and explanation of the study.
  • Demonstrate analytical and critical-thinking skills.
  • Explain the interrelationships between the environment and nature.
  • Integrate theory and practice of the discipline within the analysis.

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Case Study Outline

Let's look at the structure of an outline based on the issue of the alcoholic addiction of 30 people.

Introduction

  • Statement of the issue: Alcoholism is a disease rather than a weakness of character.
  • Presentation of the problem: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there.
  • Explanation of the terms: In the past, alcoholism was commonly referred to as alcohol dependence or alcohol addiction. Alcoholism is now the more severe stage of this addiction in the disorder spectrum.
  • Hypotheses: Drinking in excess can lead to the use of other drugs.
  • Importance of your story: How the information you present can help people with their addictions.
  • Background of the story: Include an explanation of why you chose this topic.
  • Presentation of analysis and data: Describe the criteria for choosing 30 candidates, the structure of the interview, and the outcomes.
  • Strong argument 1: ex. X% of candidates dealing with anxiety and depression...
  • Strong argument 2: ex. X amount of people started drinking by their mid-teens.
  • Strong argument 3: ex. X% of respondents’ parents had issues with alcohol.
  • Concluding statement: I have researched if alcoholism is a disease and found out that…
  • Recommendations: Ways and actions for preventing alcohol use.

Writing a Case Study Draft

After you’ve done your case study research and written the outline, it’s time to focus on the draft. In a draft, you have to develop and write your case study by using: the data which you collected throughout the research, interviews, and the analysis processes that were undertaken. Follow these rules for the draft:

How to Write a Case Study

  • Your draft should contain at least 4 sections: an introduction; a body where you should include background information, an explanation of why you decided to do this case study, and a presentation of your main findings; a conclusion where you present data; and references.
  • In the introduction, you should set the pace very clearly. You can even raise a question or quote someone you interviewed in the research phase. It must provide adequate background information on the topic. The background may include analyses of previous studies on your topic. Include the aim of your case here as well. Think of it as a thesis statement. The aim must describe the purpose of your work—presenting the issues that you want to tackle. Include background information, such as photos or videos you used when doing the research.
  • Describe your unique research process, whether it was through interviews, observations, academic journals, etc. The next point includes providing the results of your research. Tell the audience what you found out. Why is this important, and what could be learned from it? Discuss the real implications of the problem and its significance in the world.
  • Include quotes and data (such as findings, percentages, and awards). This will add a personal touch and better credibility to the case you present. Explain what results you find during your interviews in regards to the problem and how it developed. Also, write about solutions which have already been proposed by other people who have already written about this case.
  • At the end of your case study, you should offer possible solutions, but don’t worry about solving them yourself.

Use Data to Illustrate Key Points in Your Case Study

Even though your case study is a story, it should be based on evidence. Use as much data as possible to illustrate your point. Without the right data, your case study may appear weak and the readers may not be able to relate to your issue as much as they should. Let's see the examples from essay writing service :

‍ With data: Alcoholism is affecting more than 14 million people in the USA, which makes it the third most common mental illness there. Without data: A lot of people suffer from alcoholism in the United States.

Try to include as many credible sources as possible. You may have terms or sources that could be hard for other cultures to understand. If this is the case, you should include them in the appendix or Notes for the Instructor or Professor.

Finalizing the Draft: Checklist

After you finish drafting your case study, polish it up by answering these ‘ask yourself’ questions and think about how to end your case study:

  • Check that you follow the correct case study format, also in regards to text formatting.
  • Check that your work is consistent with its referencing and citation style.
  • Micro-editing — check for grammar and spelling issues.
  • Macro-editing — does ‘the big picture’ come across to the reader? Is there enough raw data, such as real-life examples or personal experiences? Have you made your data collection process completely transparent? Does your analysis provide a clear conclusion, allowing for further research and practice?

Problems to avoid:

  • Overgeneralization – Do not go into further research that deviates from the main problem.
  • Failure to Document Limitations – Just as you have to clearly state the limitations of a general research study, you must describe the specific limitations inherent in the subject of analysis.
  • Failure to Extrapolate All Possible Implications – Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings.

How to Create a Title Page and Cite a Case Study

Let's see how to create an awesome title page.

Your title page depends on the prescribed citation format. The title page should include:

  • A title that attracts some attention and describes your study
  • The title should have the words “case study” in it
  • The title should range between 5-9 words in length
  • Your name and contact information
  • Your finished paper should be only 500 to 1,500 words in length. With this type of assignment, write effectively and avoid fluff.

Here is a template for the APA and MLA format title page:

There are some cases when you need to cite someone else's study in your own one – therefore, you need to master how to cite a case study. A case study is like a research paper when it comes to citations. You can cite it like you cite a book, depending on what style you need.

Citation Example in MLA ‍ Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies. Boston: Harvard Business Publishing, 2008. Print.
Citation Example in APA ‍ Hill, L., Khanna, T., & Stecker, E. A. (2008). HCL Technologies. Boston: Harvard Business Publishing.
Citation Example in Chicago Hill, Linda, Tarun Khanna, and Emily A. Stecker. HCL Technologies.

Case Study Examples

To give you an idea of a professional case study example, we gathered and linked some below.

Eastman Kodak Case Study

Case Study Example: Audi Trains Mexican Autoworkers in Germany

To conclude, a case study is one of the best methods of getting an overview of what happened to a person, a group, or a situation in practice. It allows you to have an in-depth glance at the real-life problems that businesses, healthcare industry, criminal justice, etc. may face. This insight helps us look at such situations in a different light. This is because we see scenarios that we otherwise would not, without necessarily being there. If you need custom essays , try our research paper writing services .

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A case study research paper examines a person, place, event, condition, phenomenon, or other type of subject of analysis in order to extrapolate  key themes and results that help predict future trends, illuminate previously hidden issues that can be applied to practice, and/or provide a means for understanding an important research problem with greater clarity. A case study research paper usually examines a single subject of analysis, but case study papers can also be designed as a comparative investigation that shows relationships between two or more subjects. The methods used to study a case can rest within a quantitative, qualitative, or mixed-method investigative paradigm.

Case Studies. Writing@CSU. Colorado State University; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010 ; “What is a Case Study?” In Swanborn, Peter G. Case Study Research: What, Why and How? London: SAGE, 2010.

How to Approach Writing a Case Study Research Paper

General information about how to choose a topic to investigate can be found under the " Choosing a Research Problem " tab in the Organizing Your Social Sciences Research Paper writing guide. Review this page because it may help you identify a subject of analysis that can be investigated using a case study design.

However, identifying a case to investigate involves more than choosing the research problem . A case study encompasses a problem contextualized around the application of in-depth analysis, interpretation, and discussion, often resulting in specific recommendations for action or for improving existing conditions. As Seawright and Gerring note, practical considerations such as time and access to information can influence case selection, but these issues should not be the sole factors used in describing the methodological justification for identifying a particular case to study. Given this, selecting a case includes considering the following:

  • The case represents an unusual or atypical example of a research problem that requires more in-depth analysis? Cases often represent a topic that rests on the fringes of prior investigations because the case may provide new ways of understanding the research problem. For example, if the research problem is to identify strategies to improve policies that support girl's access to secondary education in predominantly Muslim nations, you could consider using Azerbaijan as a case study rather than selecting a more obvious nation in the Middle East. Doing so may reveal important new insights into recommending how governments in other predominantly Muslim nations can formulate policies that support improved access to education for girls.
  • The case provides important insight or illuminate a previously hidden problem? In-depth analysis of a case can be based on the hypothesis that the case study will reveal trends or issues that have not been exposed in prior research or will reveal new and important implications for practice. For example, anecdotal evidence may suggest drug use among homeless veterans is related to their patterns of travel throughout the day. Assuming prior studies have not looked at individual travel choices as a way to study access to illicit drug use, a case study that observes a homeless veteran could reveal how issues of personal mobility choices facilitate regular access to illicit drugs. Note that it is important to conduct a thorough literature review to ensure that your assumption about the need to reveal new insights or previously hidden problems is valid and evidence-based.
  • The case challenges and offers a counter-point to prevailing assumptions? Over time, research on any given topic can fall into a trap of developing assumptions based on outdated studies that are still applied to new or changing conditions or the idea that something should simply be accepted as "common sense," even though the issue has not been thoroughly tested in current practice. A case study analysis may offer an opportunity to gather evidence that challenges prevailing assumptions about a research problem and provide a new set of recommendations applied to practice that have not been tested previously. For example, perhaps there has been a long practice among scholars to apply a particular theory in explaining the relationship between two subjects of analysis. Your case could challenge this assumption by applying an innovative theoretical framework [perhaps borrowed from another discipline] to explore whether this approach offers new ways of understanding the research problem. Taking a contrarian stance is one of the most important ways that new knowledge and understanding develops from existing literature.
  • The case provides an opportunity to pursue action leading to the resolution of a problem? Another way to think about choosing a case to study is to consider how the results from investigating a particular case may result in findings that reveal ways in which to resolve an existing or emerging problem. For example, studying the case of an unforeseen incident, such as a fatal accident at a railroad crossing, can reveal hidden issues that could be applied to preventative measures that contribute to reducing the chance of accidents in the future. In this example, a case study investigating the accident could lead to a better understanding of where to strategically locate additional signals at other railroad crossings so as to better warn drivers of an approaching train, particularly when visibility is hindered by heavy rain, fog, or at night.
  • The case offers a new direction in future research? A case study can be used as a tool for an exploratory investigation that highlights the need for further research about the problem. A case can be used when there are few studies that help predict an outcome or that establish a clear understanding about how best to proceed in addressing a problem. For example, after conducting a thorough literature review [very important!], you discover that little research exists showing the ways in which women contribute to promoting water conservation in rural communities of east central Africa. A case study of how women contribute to saving water in a rural village of Uganda can lay the foundation for understanding the need for more thorough research that documents how women in their roles as cooks and family caregivers think about water as a valuable resource within their community. This example of a case study could also point to the need for scholars to build new theoretical frameworks around the topic [e.g., applying feminist theories of work and family to the issue of water conservation].

Eisenhardt, Kathleen M. “Building Theories from Case Study Research.” Academy of Management Review 14 (October 1989): 532-550; Emmel, Nick. Sampling and Choosing Cases in Qualitative Research: A Realist Approach . Thousand Oaks, CA: SAGE Publications, 2013; Gerring, John. “What Is a Case Study and What Is It Good for?” American Political Science Review 98 (May 2004): 341-354; Mills, Albert J. , Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Seawright, Jason and John Gerring. "Case Selection Techniques in Case Study Research." Political Research Quarterly 61 (June 2008): 294-308.

Structure and Writing Style

The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case studies may also be used to reveal best practices, highlight key programs, or investigate interesting aspects of professional work.

In general, the structure of a case study research paper is not all that different from a standard college-level research paper. However, there are subtle differences you should be aware of. Here are the key elements to organizing and writing a case study research paper.

I.  Introduction

As with any research paper, your introduction should serve as a roadmap for your readers to ascertain the scope and purpose of your study . The introduction to a case study research paper, however, should not only describe the research problem and its significance, but you should also succinctly describe why the case is being used and how it relates to addressing the problem. The two elements should be linked. With this in mind, a good introduction answers these four questions:

  • What is being studied? Describe the research problem and describe the subject of analysis [the case] you have chosen to address the problem. Explain how they are linked and what elements of the case will help to expand knowledge and understanding about the problem.
  • Why is this topic important to investigate? Describe the significance of the research problem and state why a case study design and the subject of analysis that the paper is designed around is appropriate in addressing the problem.
  • What did we know about this topic before I did this study? Provide background that helps lead the reader into the more in-depth literature review to follow. If applicable, summarize prior case study research applied to the research problem and why it fails to adequately address the problem. Describe why your case will be useful. If no prior case studies have been used to address the research problem, explain why you have selected this subject of analysis.
  • How will this study advance new knowledge or new ways of understanding? Explain why your case study will be suitable in helping to expand knowledge and understanding about the research problem.

Each of these questions should be addressed in no more than a few paragraphs. Exceptions to this can be when you are addressing a complex research problem or subject of analysis that requires more in-depth background information.

II.  Literature Review

The literature review for a case study research paper is generally structured the same as it is for any college-level research paper. The difference, however, is that the literature review is focused on providing background information and  enabling historical interpretation of the subject of analysis in relation to the research problem the case is intended to address . This includes synthesizing studies that help to:

  • Place relevant works in the context of their contribution to understanding the case study being investigated . This would involve summarizing studies that have used a similar subject of analysis to investigate the research problem. If there is literature using the same or a very similar case to study, you need to explain why duplicating past research is important [e.g., conditions have changed; prior studies were conducted long ago, etc.].
  • Describe the relationship each work has to the others under consideration that informs the reader why this case is applicable . Your literature review should include a description of any works that support using the case to investigate the research problem and the underlying research questions.
  • Identify new ways to interpret prior research using the case study . If applicable, review any research that has examined the research problem using a different research design. Explain how your use of a case study design may reveal new knowledge or a new perspective or that can redirect research in an important new direction.
  • Resolve conflicts amongst seemingly contradictory previous studies . This refers to synthesizing any literature that points to unresolved issues of concern about the research problem and describing how the subject of analysis that forms the case study can help resolve these existing contradictions.
  • Point the way in fulfilling a need for additional research . Your review should examine any literature that lays a foundation for understanding why your case study design and the subject of analysis around which you have designed your study may reveal a new way of approaching the research problem or offer a perspective that points to the need for additional research.
  • Expose any gaps that exist in the literature that the case study could help to fill . Summarize any literature that not only shows how your subject of analysis contributes to understanding the research problem, but how your case contributes to a new way of understanding the problem that prior research has failed to do.
  • Locate your own research within the context of existing literature [very important!] . Collectively, your literature review should always place your case study within the larger domain of prior research about the problem. The overarching purpose of reviewing pertinent literature in a case study paper is to demonstrate that you have thoroughly identified and synthesized prior studies in relation to explaining the relevance of the case in addressing the research problem.

III.  Method

In this section, you explain why you selected a particular case [i.e., subject of analysis] and the strategy you used to identify and ultimately decide that your case was appropriate in addressing the research problem. The way you describe the methods used varies depending on the type of subject of analysis that constitutes your case study.

If your subject of analysis is an incident or event . In the social and behavioral sciences, the event or incident that represents the case to be studied is usually bounded by time and place, with a clear beginning and end and with an identifiable location or position relative to its surroundings. The subject of analysis can be a rare or critical event or it can focus on a typical or regular event. The purpose of studying a rare event is to illuminate new ways of thinking about the broader research problem or to test a hypothesis. Critical incident case studies must describe the method by which you identified the event and explain the process by which you determined the validity of this case to inform broader perspectives about the research problem or to reveal new findings. However, the event does not have to be a rare or uniquely significant to support new thinking about the research problem or to challenge an existing hypothesis. For example, Walo, Bull, and Breen conducted a case study to identify and evaluate the direct and indirect economic benefits and costs of a local sports event in the City of Lismore, New South Wales, Australia. The purpose of their study was to provide new insights from measuring the impact of a typical local sports event that prior studies could not measure well because they focused on large "mega-events." Whether the event is rare or not, the methods section should include an explanation of the following characteristics of the event: a) when did it take place; b) what were the underlying circumstances leading to the event; and, c) what were the consequences of the event in relation to the research problem.

If your subject of analysis is a person. Explain why you selected this particular individual to be studied and describe what experiences they have had that provide an opportunity to advance new understandings about the research problem. Mention any background about this person which might help the reader understand the significance of their experiences that make them worthy of study. This includes describing the relationships this person has had with other people, institutions, and/or events that support using them as the subject for a case study research paper. It is particularly important to differentiate the person as the subject of analysis from others and to succinctly explain how the person relates to examining the research problem [e.g., why is one politician in a particular local election used to show an increase in voter turnout from any other candidate running in the election]. Note that these issues apply to a specific group of people used as a case study unit of analysis [e.g., a classroom of students].

If your subject of analysis is a place. In general, a case study that investigates a place suggests a subject of analysis that is unique or special in some way and that this uniqueness can be used to build new understanding or knowledge about the research problem. A case study of a place must not only describe its various attributes relevant to the research problem [e.g., physical, social, historical, cultural, economic, political], but you must state the method by which you determined that this place will illuminate new understandings about the research problem. It is also important to articulate why a particular place as the case for study is being used if similar places also exist [i.e., if you are studying patterns of homeless encampments of veterans in open spaces, explain why you are studying Echo Park in Los Angeles rather than Griffith Park?]. If applicable, describe what type of human activity involving this place makes it a good choice to study [e.g., prior research suggests Echo Park has more homeless veterans].

If your subject of analysis is a phenomenon. A phenomenon refers to a fact, occurrence, or circumstance that can be studied or observed but with the cause or explanation to be in question. In this sense, a phenomenon that forms your subject of analysis can encompass anything that can be observed or presumed to exist but is not fully understood. In the social and behavioral sciences, the case usually focuses on human interaction within a complex physical, social, economic, cultural, or political system. For example, the phenomenon could be the observation that many vehicles used by ISIS fighters are small trucks with English language advertisements on them. The research problem could be that ISIS fighters are difficult to combat because they are highly mobile. The research questions could be how and by what means are these vehicles used by ISIS being supplied to the militants and how might supply lines to these vehicles be cut off? How might knowing the suppliers of these trucks reveal larger networks of collaborators and financial support? A case study of a phenomenon most often encompasses an in-depth analysis of a cause and effect that is grounded in an interactive relationship between people and their environment in some way.

NOTE:   The choice of the case or set of cases to study cannot appear random. Evidence that supports the method by which you identified and chose your subject of analysis should clearly support investigation of the research problem and linked to key findings from your literature review. Be sure to cite any studies that helped you determine that the case you chose was appropriate for examining the problem.

IV.  Discussion

The main elements of your discussion section are generally the same as any research paper, but centered around interpreting and drawing conclusions about the key findings from your analysis of the case study. Note that a general social sciences research paper may contain a separate section to report findings. However, in a paper designed around a case study, it is common to combine a description of the results with the discussion about their implications. The objectives of your discussion section should include the following:

Reiterate the Research Problem/State the Major Findings Briefly reiterate the research problem you are investigating and explain why the subject of analysis around which you designed the case study were used. You should then describe the findings revealed from your study of the case using direct, declarative, and succinct proclamation of the study results. Highlight any findings that were unexpected or especially profound.

Explain the Meaning of the Findings and Why They are Important Systematically explain the meaning of your case study findings and why you believe they are important. Begin this part of the section by repeating what you consider to be your most important or surprising finding first, then systematically review each finding. Be sure to thoroughly extrapolate what your analysis of the case can tell the reader about situations or conditions beyond the actual case that was studied while, at the same time, being careful not to misconstrue or conflate a finding that undermines the external validity of your conclusions.

Relate the Findings to Similar Studies No study in the social sciences is so novel or possesses such a restricted focus that it has absolutely no relation to previously published research. The discussion section should relate your case study results to those found in other studies, particularly if questions raised from prior studies served as the motivation for choosing your subject of analysis. This is important because comparing and contrasting the findings of other studies helps support the overall importance of your results and it highlights how and in what ways your case study design and the subject of analysis differs from prior research about the topic.

Consider Alternative Explanations of the Findings Remember that the purpose of social science research is to discover and not to prove. When writing the discussion section, you should carefully consider all possible explanations revealed by the case study results, rather than just those that fit your hypothesis or prior assumptions and biases. Be alert to what the in-depth analysis of the case may reveal about the research problem, including offering a contrarian perspective to what scholars have stated in prior research if that is how the findings can be interpreted from your case.

Acknowledge the Study's Limitations You can state the study's limitations in the conclusion section of your paper but describing the limitations of your subject of analysis in the discussion section provides an opportunity to identify the limitations and explain why they are not significant. This part of the discussion section should also note any unanswered questions or issues your case study could not address. More detailed information about how to document any limitations to your research can be found here .

Suggest Areas for Further Research Although your case study may offer important insights about the research problem, there are likely additional questions related to the problem that remain unanswered or findings that unexpectedly revealed themselves as a result of your in-depth analysis of the case. Be sure that the recommendations for further research are linked to the research problem and that you explain why your recommendations are valid in other contexts and based on the original assumptions of your study.

V.  Conclusion

As with any research paper, you should summarize your conclusion in clear, simple language; emphasize how the findings from your case study differs from or supports prior research and why. Do not simply reiterate the discussion section. Provide a synthesis of key findings presented in the paper to show how these converge to address the research problem. If you haven't already done so in the discussion section, be sure to document the limitations of your case study and any need for further research.

The function of your paper's conclusion is to: 1) reiterate the main argument supported by the findings from your case study; 2) state clearly the context, background, and necessity of pursuing the research problem using a case study design in relation to an issue, controversy, or a gap found from reviewing the literature; and, 3) provide a place to persuasively and succinctly restate the significance of your research problem, given that the reader has now been presented with in-depth information about the topic.

Consider the following points to help ensure your conclusion is appropriate:

  • If the argument or purpose of your paper is complex, you may need to summarize these points for your reader.
  • If prior to your conclusion, you have not yet explained the significance of your findings or if you are proceeding inductively, use the conclusion of your paper to describe your main points and explain their significance.
  • Move from a detailed to a general level of consideration of the case study's findings that returns the topic to the context provided by the introduction or within a new context that emerges from your case study findings.

Note that, depending on the discipline you are writing in or the preferences of your professor, the concluding paragraph may contain your final reflections on the evidence presented as it applies to practice or on the essay's central research problem. However, the nature of being introspective about the subject of analysis you have investigated will depend on whether you are explicitly asked to express your observations in this way.

Problems to Avoid

Overgeneralization One of the goals of a case study is to lay a foundation for understanding broader trends and issues applied to similar circumstances. However, be careful when drawing conclusions from your case study. They must be evidence-based and grounded in the results of the study; otherwise, it is merely speculation. Looking at a prior example, it would be incorrect to state that a factor in improving girls access to education in Azerbaijan and the policy implications this may have for improving access in other Muslim nations is due to girls access to social media if there is no documentary evidence from your case study to indicate this. There may be anecdotal evidence that retention rates were better for girls who were engaged with social media, but this observation would only point to the need for further research and would not be a definitive finding if this was not a part of your original research agenda.

Failure to Document Limitations No case is going to reveal all that needs to be understood about a research problem. Therefore, just as you have to clearly state the limitations of a general research study , you must describe the specific limitations inherent in the subject of analysis. For example, the case of studying how women conceptualize the need for water conservation in a village in Uganda could have limited application in other cultural contexts or in areas where fresh water from rivers or lakes is plentiful and, therefore, conservation is understood more in terms of managing access rather than preserving access to a scarce resource.

Failure to Extrapolate All Possible Implications Just as you don't want to over-generalize from your case study findings, you also have to be thorough in the consideration of all possible outcomes or recommendations derived from your findings. If you do not, your reader may question the validity of your analysis, particularly if you failed to document an obvious outcome from your case study research. For example, in the case of studying the accident at the railroad crossing to evaluate where and what types of warning signals should be located, you failed to take into consideration speed limit signage as well as warning signals. When designing your case study, be sure you have thoroughly addressed all aspects of the problem and do not leave gaps in your analysis that leave the reader questioning the results.

Case Studies. Writing@CSU. Colorado State University; Gerring, John. Case Study Research: Principles and Practices . New York: Cambridge University Press, 2007; Merriam, Sharan B. Qualitative Research and Case Study Applications in Education . Rev. ed. San Francisco, CA: Jossey-Bass, 1998; Miller, Lisa L. “The Use of Case Studies in Law and Social Science Research.” Annual Review of Law and Social Science 14 (2018): TBD; Mills, Albert J., Gabrielle Durepos, and Eiden Wiebe, editors. Encyclopedia of Case Study Research . Thousand Oaks, CA: SAGE Publications, 2010; Putney, LeAnn Grogan. "Case Study." In Encyclopedia of Research Design , Neil J. Salkind, editor. (Thousand Oaks, CA: SAGE Publications, 2010), pp. 116-120; Simons, Helen. Case Study Research in Practice . London: SAGE Publications, 2009;  Kratochwill,  Thomas R. and Joel R. Levin, editors. Single-Case Research Design and Analysis: New Development for Psychology and Education .  Hilldsale, NJ: Lawrence Erlbaum Associates, 1992; Swanborn, Peter G. Case Study Research: What, Why and How? London : SAGE, 2010; Yin, Robert K. Case Study Research: Design and Methods . 6th edition. Los Angeles, CA, SAGE Publications, 2014; Walo, Maree, Adrian Bull, and Helen Breen. “Achieving Economic Benefits at Local Events: A Case Study of a Local Sports Event.” Festival Management and Event Tourism 4 (1996): 95-106.

Writing Tip

At Least Five Misconceptions about Case Study Research

Social science case studies are often perceived as limited in their ability to create new knowledge because they are not randomly selected and findings cannot be generalized to larger populations. Flyvbjerg examines five misunderstandings about case study research and systematically "corrects" each one. To quote, these are:

Misunderstanding 1 :  General, theoretical [context-independent] knowledge is more valuable than concrete, practical [context-dependent] knowledge. Misunderstanding 2 :  One cannot generalize on the basis of an individual case; therefore, the case study cannot contribute to scientific development. Misunderstanding 3 :  The case study is most useful for generating hypotheses; that is, in the first stage of a total research process, whereas other methods are more suitable for hypotheses testing and theory building. Misunderstanding 4 :  The case study contains a bias toward verification, that is, a tendency to confirm the researcher’s preconceived notions. Misunderstanding 5 :  It is often difficult to summarize and develop general propositions and theories on the basis of specific case studies [p. 221].

While writing your paper, think introspectively about how you addressed these misconceptions because to do so can help you strengthen the validity and reliability of your research by clarifying issues of case selection, the testing and challenging of existing assumptions, the interpretation of key findings, and the summation of case outcomes. Think of a case study research paper as a complete, in-depth narrative about the specific properties and key characteristics of your subject of analysis applied to the research problem.

Flyvbjerg, Bent. “Five Misunderstandings About Case-Study Research.” Qualitative Inquiry 12 (April 2006): 219-245.

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Types of Case Studies

There are several different types of case studies, as well as several types of subjects of case studies. We will investigate each type in this article.

Different Types of Case Studies

There are several types of case studies, each differing from each other based on the hypothesis and/or thesis to be proved. It is also possible for types of case studies to overlap each other.

Each of the following types of cases can be used in any field or discipline. Whether it is psychology, business or the arts, the type of case study can apply to any field.

Explanatory

The explanatory case study focuses on an explanation for a question or a phenomenon. Basically put, an explanatory case study is 1 + 1 = 2. The results are not up for interpretation.

A case study with a person or group would not be explanatory, as with humans, there will always be variables. There are always small variances that cannot be explained.

However, event case studies can be explanatory. For example, let's say a certain automobile has a series of crashes that are caused by faulty brakes. All of the crashes are a result of brakes not being effective on icy roads.

What kind of case study is explanatory? Think of an example of an explanatory case study that could be done today

When developing the case study, the researcher will explain the crash, and the detailed causes of the brake failure. They will investigate what actions caused the brakes to fail, and what actions could have been taken to prevent the failure.

Other car companies could then use this case study to better understand what makes brakes fail. When designing safer products, looking to past failures is an excellent way to ensure similar mistakes are not made.

The same can be said for other safety issues in cars. There was a time when cars did not have seatbelts. The process to get seatbelts required in all cars started with a case study! The same can be said about airbags and collapsible steering columns. They all began with a case study that lead to larger research, and eventual change.

Exploratory

An exploratory case study is usually the precursor to a formal, large-scale research project. The case study's goal is to prove that further investigation is necessary.

For example, an exploratory case study could be done on veterans coming home from active combat. Researchers are aware that these vets have PTSD, and are aware that the actions of war are what cause PTSD. Beyond that, they do not know if certain wartime activities are more likely to contribute to PTSD than others.

For an exploratory case study, the researcher could develop a study that certain war events are more likely to cause PTSD. Once that is demonstrated, a large-scale research project could be done to determine which events are most likely to cause PTSD.

Exploratory case studies are very popular in psychology and the social sciences. Psychologists are always looking for better ways to treat their patients, and exploratory studies allow them to research new ideas or theories.

Multiple-Case Studies or Collective Studies

Multiple case or collective studies use information from different studies to formulate the case for a new study. The use of past studies allows additional information without needing to spend more time and money on additional studies.

Using the PTSD issue again is an excellent example of a collective study. When studying what contributes most to wartime PTSD, a researcher could use case studies from different war. For instance, studies about PTSD in WW2 vets, Persian Gulf War vets, and Vietnam vets could provide an excellent sampling of which wartime activities are most likely to cause PTSD.

If a multiple case study on vets was done with vets from the Vietnam War, the Persian Gulf War, and the Iraq War, and it was determined the vets from Vietnam had much less PTSD, what could be inferred?

Furthermore, this type of study could uncover differences as well. For example, a researcher might find that veterans who serve in the Middle East are more likely to suffer a certain type of ailment. Or perhaps, that veterans who served with large platoons were more likely to suffer from PTSD than veterans who served in smaller platoons.

An intrinsic case study is the study of a case wherein the subject itself is the primary interest. The "Genie" case is an example of this. The study wasn't so much about psychology, but about Genie herself, and how her experiences shaped who she was.

Genie is the topic. Genie is what the researchers are interested in, and what their readers will be most interested in. When the researchers started the study, they didn't know what they would find.

They asked the question…"If a child is never introduced to language during the crucial first years of life, can they acquire language skills when they are older?" When they met Genie, they didn't know the answer to that question.

Instrumental

An instrumental case study uses a case to gain insights into a phenomenon. For example, a researcher interested in child obesity rates might set up a study with middle school students and an exercise program. In this case, the children and the exercise program are not the focus. The focus is learning the relationship between children and exercise, and why certain children become obese.

What is an example of an instrumental case study?

Focus on the results, not the topic!

Types of Subjects of Case Studies

There are generally five different types of case studies, and the subjects that they address. Every case study, whether explanatory or exploratory, or intrinsic or instrumental, fits into one of these five groups. These are:

Person – This type of study focuses on one particular individual. This case study would use several types of research to determine an outcome.

The best example of a person case is the "Genie" case study. Again, "Genie" was a 13-year-old girl who was discovered by social services in Los Angeles in 1970. Her father believed her to be mentally retarded, and therefore locked her in a room without any kind of stimulation. She was never nourished or cared for in any way. If she made a noise, she was beaten.

When "Genie" was discovered, child development specialists wanted to learn as much as possible about how her experiences contributed to her physical, emotional and mental health. They also wanted to learn about her language skills. She had no form of language when she was found, she only grunted. The study would determine whether or not she could learn language skills at the age of 13.

Since Genie was placed in a children's hospital, many different clinicians could observe her. In addition, researchers were able to interview the few people who did have contact with Genie and would be able to gather whatever background information was available.

This case study is still one of the most valuable in all of child development. Since it would be impossible to conduct this type of research with a healthy child, the information garnered from Genie's case is invaluable.

Group – This type of study focuses on a group of people. This could be a family, a group or friends, or even coworkers.

An example of this type of case study would be the uncontacted tribes of Indians in the Peruvian and Brazilian rainforest. These tribes have never had any modern contact. Therefore, there is a great interest to study them.

Scientists would be interested in just about every facet of their lives. How do they cook, how do they make clothing, how do they make tools and weapons. Also, doing psychological and emotional research would be interesting. However, because so few of these tribes exist, no one is contacting them for research. For now, all research is done observationally.

If a researcher wanted to study uncontacted Indian tribes, and could only observe the subjects, what type of observations should be made?

Location – This type of study focuses on a place, and how and why people use the place.

For example, many case studies have been done about Siberia, and the people who live there. Siberia is a cold and barren place in northern Russia, and it is considered the most difficult place to live in the world. Studying the location, and it's weather and people can help other people learn how to live with extreme weather and isolation.

Location studies can also be done on locations that are facing some kind of change. For example, a case study could be done on Alaska, and whether the state is seeing the effects of climate change.

Another type of study that could be done in Alaska is how the environment changes as population increases. Geographers and those interested in population growth often do these case studies.

Organization/Company – This type of study focuses on a business or an organization. This could include the people who work for the company, or an event that occurred at the organization.

An excellent example of this type of case study is Enron. Enron was one of the largest energy company's in the United States, when it was discovered that executives at the company were fraudulently reporting the company's accounting numbers.

Once the fraud was uncovered, investigators discovered willful and systematic corruption that caused the collapse of Enron, as well as their financial auditors, Arthur Andersen. The fraud was so severe that the top executives of the company were sentenced to prison.

This type of case study is used by accountants, auditors, financiers, as well as business students, in order to learn how such a large company could get away with committing such a serious case of corporate fraud for as long as they did. It can also be looked at from a psychological standpoint, as it is interesting to learn why the executives took the large risks that they took.

Most company or organization case studies are done for business purposes. In fact, in many business schools, such as Harvard Business School, students learn by the case method, which is the study of case studies. They learn how to solve business problems by studying the cases of businesses that either survived the same problem, or one that didn't survive the problem.

Event – This type of study focuses on an event, whether cultural or societal, and how it affects those that are affected by it. An example would be the Tylenol cyanide scandal. This event affected Johnson & Johnson, the parent company, as well as the public at large.

The case study would detail the events of the scandal, and more specifically, what management at Johnson & Johnson did to correct the problem. To this day, when a company experiences a large public relations scandal, they look to the Tylenol case study to learn how they managed to survive the scandal.

A very popular topic for case studies was the events of September 11 th . There were studies in almost all of the different types of research studies.

Obviously the event itself was a very popular topic. It was important to learn what lead up to the event, and how best to proven it from happening in the future. These studies are not only important to the U.S. government, but to other governments hoping to prevent terrorism in their countries.

Planning A Case Study

You have decided that you want to research and write a case study. Now what? In this section you will learn how to plan and organize a research case study.

Selecting a Case

The first step is to choose the subject, topic or case. You will want to choose a topic that is interesting to you, and a topic that would be of interest to your potential audience. Ideally you have a passion for the topic, as then you will better understand the issues surrounding the topic, and which resources would be most successful in the study.

You also must choose a topic that would be of interest to a large number of people. You want your case study to reach as large an audience as possible, and a topic that is of interest to just a few people will not have a very large reach. One of the goals of a case study is to reach as many people as possible.

Who is your audience?

Are you trying to reach the layperson? Or are you trying to reach other professionals in your field? Your audience will help determine the topic you choose.

If you are writing a case study that is looking for ways to lower rates of child obesity, who is your audience?

If you are writing a psychology case study, you must consider whether your audience will have the intellectual skills to understand the information in the case. Does your audience know the vocabulary of psychology? Do they understand the processes and structure of the field?

You want your audience to have as much general knowledge as possible. When it comes time to write the case study, you may have to spend some time defining and explaining terms that might be unfamiliar to the audience.

Lastly, when selecting a topic you do not want to choose a topic that is very old. Current topics are always the most interesting, so if your topic is more than 5-10 years old, you might want to consider a newer topic. If you choose an older topic, you must ask yourself what new and valuable information do you bring to the older topic, and is it relevant and necessary.

Determine Research Goals

What type of case study do you plan to do?

An illustrative case study will examine an unfamiliar case in order to help others understand it. For example, a case study of a veteran with PTSD can be used to help new therapists better understand what veterans experience.

An exploratory case study is a preliminary project that will be the precursor to a larger study in the future. For example, a case study could be done challenging the efficacy of different therapy methods for vets with PTSD. Once the study is complete, a larger study could be done on whichever method was most effective.

A critical instance case focuses on a unique case that doesn't have a predetermined purpose. For example, a vet with an incredibly severe case of PTSD could be studied to find ways to treat his condition.

Ethics are a large part of the case study process, and most case studies require ethical approval. This approval usually comes from the institution or department the researcher works for. Many universities and research institutions have ethics oversight departments. They will require you to prove that you will not harm your study subjects or participants.

This should be done even if the case study is on an older subject. Sometimes publishing new studies can cause harm to the original participants. Regardless of your personal feelings, it is essential the project is brought to the ethics department to ensure your project can proceed safely.

Developing the Case Study

Once you have your topic, it is time to start planning and developing the study. This process will be different depending on what type of case study you are planning to do. For thissection, we will assume a psychological case study, as most case studies are based on the psychological model.

Once you have the topic, it is time to ask yourself some questions. What question do you want to answer with the study?

For example, a researcher is considering a case study about PTSD in veterans. The topic is PTSD in veterans. What questions could be asked?

Do veterans from Middle Eastern wars suffer greater instances of PTSD?

Do younger soldiers have higher instances of PTSD?

Does the length of the tour effect the severity of PTSD?

Each of these questions is a viable question, and finding the answers, or the possible answers, would be helpful for both psychologists and veterans who suffer from PTSD.

Research Notebook

1. What is the background of the case study? Who requested the study to be done and why? What industry is the study in, and where will the study take place?

2. What is the problem that needs a solution? What is the situation, and what are the risks?

3. What questions are required to analyze the problem? What questions might the reader of the study have? What questions might colleagues have?

4. What tools are required to analyze the problem? Is data analysis necessary?

5. What is your current knowledge about the problem or situation? How much background information do you need to procure? How will you obtain this background info?

6. What other information do you need to know to successfully complete the study?

7. How do you plan to present the report? Will it be a simple written report, or will you add PowerPoint presentations or images or videos? When is the report due? Are you giving yourself enough time to complete the project?

The research notebook is the heart of the study. Other organizational methods can be utilized, such as Microsoft Excel, but a physical notebook should always be kept as well.

Planning the Research

The most important parts of the case study are:

1. The case study's questions

2. The study's propositions

3. How information and data will be analyzed

4. The logic behind the propositions

5. How the findings will be interpreted

The study's questions should be either a "how" or "why" question, and their definition is the researchers first job. These questions will help determine the study's goals.

Not every case study has a proposition. If you are doing an exploratory study, you will not have propositions. Instead, you will have a stated purpose, which will determine whether your study is successful, or not.

How the information will be analyzed will depend on what the topic is. This would vary depending on whether it was a person, group, or organization.

When setting up your research, you will want to follow case study protocol. The protocol should have the following sections:

1. An overview of the case study, including the objectives, topic and issues.

2. Procedures for gathering information and conducting interviews.

3. Questions that will be asked during interviews and data collection.

4. A guide for the final case study report.

When deciding upon which research methods to use, these are the most important:

1. Documents and archival records

2. Interviews

3. Direct observations

4. Indirect observations, or observations of subjects

5. Physical artifacts and tools

Documents could include almost anything, including letters, memos, newspaper articles, Internet articles, other case studies, or any other document germane to the study.

Archival records can include military and service records, company or business records, survey data or census information.

Research Strategy

Before beginning the study you want a clear research strategy. Your best chance at success will be if you use an outline that describes how you will gather your data and how you will answer your research questions.

The researcher should create a list with four or five bullet points that need answers. Consider the approaches for these questions, and the different perspectives you could take.

The researcher should then choose at least two data sources (ideally more). These sources could include interviews, Internet research, and fieldwork or report collection. The more data sources used, the better the quality of the final data.

The researcher then must formulate interview questions that will result in detailed and in-depth answers that will help meet the research goals. A list of 15-20 questions is a good start, but these can and will change as the process flows.

Planning Interviews

The interview process is one of the most important parts of the case study process. But before this can begin, it is imperative the researcher gets informed consent from the subjects.

The process of informed consent means the subject understands their role in the study, and that their story will be used in the case study. You will want to have each subject complete a consent form.

The researcher must explain what the study is trying to achieve, and how their contribution will help the study. If necessary, assure the subject that their information will remain private if requested, and they do not need to use their real name if they are not comfortable with that. Pseudonyms are commonly used in case studies.

Informed Consent

The process by which permission is granted before beginning medical or psychological research

A fictitious name used to hide ones identity

It is important the researcher is clear regarding the expectations of the study participation. For example, are they comfortable on camera? Do they mind if their photo is used in the final written study.

Interviews are one of the most important sources of information for case studies. There are several types of interviews. They are:

Open-ended – This type of interview has the interviewer and subject talking to each other about the subject. The interviewer asks questions, and the subject answers them. But the subject can elaborate and add information whenever they see fit.

A researcher might meet with a subject multiple times, and use the open-ended method. This can be a great way to gain insight into events. However, the researcher mustn't rely solely on the information from the one subject, and be sure to have multiple sources.

Focused – This type of interview is used when the subject is interviewed for a short period of time, and answers a set of questions. This type of interview could be used to verify information learned in an open-ended interview with another subject. Focused interviews are normally done to confirm information, not to gain new information.

Structured – Structured interviews are similar to surveys. These are usually used when collecting data for large groups, like neighborhoods. The questions are decided before hand, and the expected answers are usually simple.

When conducting interviews, the answers are obviously important. But just as important are the observations that can be made. This is one of the reasons in-person interviews are preferable over phone interviews, or Internet or mail surveys.

Ideally, when conducing in-person interviews, more than one researcher should be present. This allows one researcher to focus on observing while the other is interviewing. This is particularly important when interviewing large groups of people.

The researcher must understand going into the case study that the information gained from the interviews might not be valuable. It is possible that once the interviews are completed, the information gained is not relevant.

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Case Study – Guide with Definition, Types & Examples

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Case-study-Definition

Case studies are used in different types of research for describing, evaluating and comparing different variables in a research problem. This approach allows researchers to gather comprehensive, multifaceted data about complex real-world situations through various sources such as interviews, observations, and document review.

A well-formulated case study guides the process and methodology of research.

Inhaltsverzeichnis

  • 1 Case Study – In a Nutshell
  • 2 Definition: Case Study
  • 3 Types of case studies
  • 4 When to perform a case study
  • 5 Case Study: Step-by-step
  • 6 Benefits and limitations of a case study

Case Study – In a Nutshell

  • Case studies can capture several perspectives or a single focus, depending on the scope of the study.
  • Researchers use case studies as a standalone approach or as part of a more extensive study.
  • Case studies contribute to the body of knowledge by exploring new focus points and questioning existing theories.

Definition: Case Study

A case study is an in-depth study of a particular phenomenon, subject or group. The study usually employs qualitative methods, although quantitative analysis may be used to measure the relationship between some variables. Case studies document every aspect of the target group or phenomenon to achieve a granular understanding through research.

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Types of case studies

There are 6 types of case studies in research. These are:

  • Illustrative – It is used to study a known phenomenon to make it easier to understand. It is one of the primary case studies which utilizes a descriptive approach to explain a phenomenon using one or more scenarios.
  • Exploratory – It is an initial study conducted before the main study. Exploratory researches are used in social sciences and focus on real-life scenarios. They are conducted to help in the formulation of research questions for complex studies.
  • Cumulative – It is primarily used in qualitative research . It can be classified as a type of data analysis. The purpose of the case study is to analyze information from existing sources to gain insights into a research problem.
  • Critical instance – It evaluates an event’s cause and effect. A critical case study investigates one or two instances to understand one occurrence rather than generalizing the situation. The case study can also be deployed to cross-examine a universal opinion.
  • Descriptive – You can use a descriptive research to build on a hypothesis. It may be used in quantitative research to ascertain relationships between a theory and the subject of a research project.
  • Intrinsic – Mainly focuses on a single subject to understand their interaction with factors around them. It is often used in psychology and healthcare research to study individuals and their unique characteristics.

Case studies can be summarized into 3 main groups for general understanding. These are:

  • Intrinsic studies to examine unique phenomena or individuals
  • Instrumental case studies to study individuals to understand a broader topic
  • Collective case studies to investigate multiple cases concurrently.

When to perform a case study

A case study is the right research design for examining and gaining precise, contextual insights about a real-world problem or scenario. It gives researchers a method of studying the main characteristics, definitions and inferences about a case.

They are appropriate for thesis and dissertations as they narrow the focus of a project. This helps to anchor the research and save time and resources by focusing on fewer variables.

Researchers may use a single in-depth case study when investigating one subject. However, several case studies may be conducted simultaneously to draw comparisons from various variables in the research problem.

Examples of research questions and their corresponding case studies:

Case Study: Step-by-step

We can break down the main steps as follows:

Step 1: Select a case

The research questions and the problem statement should present several potential cases. Choose a specific focus to ground your research. The case study should be able to:

  • Offer new insights about the subject.
  • Question or critique existing notions and assumptions.
  • Suggest practical approaches to solve a problem.
  • Propose new approaches for research in the future.

Case studies usually focus on outliers rather than deliberate sampling techniques. Thus, they often do not require representative or random samples before research.

Step 2: Build a theoretical framework

Case studies overlook general theories in favor of specific details. However, they should have some relationship with an existing theory so that the research findings contribute to the current understanding of the research subject. A theoretical framework can be used to:

  • Challenge an existing theory by investigating deviance that is not considered in the universal assumptions.
  • Expand on established theories by proposing new ideas that should be included.
  • Exemplify a given theory by showing the relationship between the case and the theory.
  • Researchers develop a theoretical framework after a literature review of relevant sources to achieve academic credibility by considering the main theories in conducting analysis.

Step 3: Collect your data

There are various research methods used in the collection of quantitative and qualitative data. Case studies are more concerned with qualitative data from interviews, examination of different literary sources and observation, although some quantitative methods can be used where necessary.

Step 4: Describe and analyze the case

You need to provide a detailed picture of the research subject by proposing a case study that incorporates the main aspects of the study. Researchers can format their findings in a thesis structure with clear sections to draw attention to analysis methods, findings and discourse.

Some case studies can be outlined in narrative prose to delve into the concepts from different perspectives and explain the definitions and consequences. Regardless of the method of presentation, it is essential to provide context and create a link between the case and the literature used in its study.

Benefits and limitations of a case study

Some of the pros and cons of case studies include:

What is a case study in research?

A case study is an in-depth investigation of a research subject, individual, or group. It is a focused research method that analyzes the causes and consequences of a determined phenomenon.

What is the importance of a theoretical framework in a case study?

A theoretical framework highlights the relevant concepts in a research theory to guide the study. It also informs the literature review process of existing primary and secondary sources of information.

When should a case study be conducted?

A case study is used to examine real-world situations. Researchers formulate case studies to identify and investigate real scenarios using existing sources and research problems that aim to study outliers of a research subject.

Where are case studies used?

Case studies are deployed in social sciences and fields such as psychology and healthcare research. They are used to provide focused conclusions in complex research problems.

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What is case study research?

Last updated

8 February 2023

Reviewed by

Cathy Heath

Suppose a company receives a spike in the number of customer complaints, or medical experts discover an outbreak of illness affecting children but are not quite sure of the reason. In both cases, carrying out a case study could be the best way to get answers.

Organization

Case studies can be carried out across different disciplines, including education, medicine, sociology, and business.

Most case studies employ qualitative methods, but quantitative methods can also be used. Researchers can then describe, compare, evaluate, and identify patterns or cause-and-effect relationships between the various variables under study. They can then use this knowledge to decide what action to take. 

Another thing to note is that case studies are generally singular in their focus. This means they narrow focus to a particular area, making them highly subjective. You cannot always generalize the results of a case study and apply them to a larger population. However, they are valuable tools to illustrate a principle or develop a thesis.

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Dovetail streamlines case study research to help you uncover and share actionable insights

  • What are the different types of case study designs?

Researchers can choose from a variety of case study designs. The design they choose is dependent on what questions they need to answer, the context of the research environment, how much data they already have, and what resources are available.

Here are the common types of case study design:

Explanatory

An explanatory case study is an initial explanation of the how or why that is behind something. This design is commonly used when studying a real-life phenomenon or event. Once the organization understands the reasons behind a phenomenon, it can then make changes to enhance or eliminate the variables causing it. 

Here is an example: How is co-teaching implemented in elementary schools? The title for a case study of this subject could be “Case Study of the Implementation of Co-Teaching in Elementary Schools.”

Descriptive

An illustrative or descriptive case study helps researchers shed light on an unfamiliar object or subject after a period of time. The case study provides an in-depth review of the issue at hand and adds real-world examples in the area the researcher wants the audience to understand. 

The researcher makes no inferences or causal statements about the object or subject under review. This type of design is often used to understand cultural shifts.

Here is an example: How did people cope with the 2004 Indian Ocean Tsunami? This case study could be titled "A Case Study of the 2004 Indian Ocean Tsunami and its Effect on the Indonesian Population."

Exploratory

Exploratory research is also called a pilot case study. It is usually the first step within a larger research project, often relying on questionnaires and surveys . Researchers use exploratory research to help narrow down their focus, define parameters, draft a specific research question , and/or identify variables in a larger study. This research design usually covers a wider area than others, and focuses on the ‘what’ and ‘who’ of a topic.

Here is an example: How do nutrition and socialization in early childhood affect learning in children? The title of the exploratory study may be “Case Study of the Effects of Nutrition and Socialization on Learning in Early Childhood.”

An intrinsic case study is specifically designed to look at a unique and special phenomenon. At the start of the study, the researcher defines the phenomenon and the uniqueness that differentiates it from others. 

In this case, researchers do not attempt to generalize, compare, or challenge the existing assumptions. Instead, they explore the unique variables to enhance understanding. Here is an example: “Case Study of Volcanic Lightning.”

This design can also be identified as a cumulative case study. It uses information from past studies or observations of groups of people in certain settings as the foundation of the new study. Given that it takes multiple areas into account, it allows for greater generalization than a single case study. 

The researchers also get an in-depth look at a particular subject from different viewpoints.  Here is an example: “Case Study of how PTSD affected Vietnam and Gulf War Veterans Differently Due to Advances in Military Technology.”

Critical instance

A critical case study incorporates both explanatory and intrinsic study designs. It does not have predetermined purposes beyond an investigation of the said subject. It can be used for a deeper explanation of the cause-and-effect relationship. It can also be used to question a common assumption or myth. 

The findings can then be used further to generalize whether they would also apply in a different environment.  Here is an example: “What Effect Does Prolonged Use of Social Media Have on the Mind of American Youth?”

Instrumental

Instrumental research attempts to achieve goals beyond understanding the object at hand. Researchers explore a larger subject through different, separate studies and use the findings to understand its relationship to another subject. This type of design also provides insight into an issue or helps refine a theory. 

For example, you may want to determine if violent behavior in children predisposes them to crime later in life. The focus is on the relationship between children and violent behavior, and why certain children do become violent. Here is an example: “Violence Breeds Violence: Childhood Exposure and Participation in Adult Crime.”

Evaluation case study design is employed to research the effects of a program, policy, or intervention, and assess its effectiveness and impact on future decision-making. 

For example, you might want to see whether children learn times tables quicker through an educational game on their iPad versus a more teacher-led intervention. Here is an example: “An Investigation of the Impact of an iPad Multiplication Game for Primary School Children.” 

  • When do you use case studies?

Case studies are ideal when you want to gain a contextual, concrete, or in-depth understanding of a particular subject. It helps you understand the characteristics, implications, and meanings of the subject.

They are also an excellent choice for those writing a thesis or dissertation, as they help keep the project focused on a particular area when resources or time may be too limited to cover a wider one. You may have to conduct several case studies to explore different aspects of the subject in question and understand the problem.

  • What are the steps to follow when conducting a case study?

1. Select a case

Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research.

2. Create a theoretical framework

While you will be focusing on a specific detail, the case study design you choose should be linked to existing knowledge on the topic. This prevents it from becoming an isolated description and allows for enhancing the existing information. 

It may expand the current theory by bringing up new ideas or concepts, challenge established assumptions, or exemplify a theory by exploring how it answers the problem at hand. A theoretical framework starts with a literature review of the sources relevant to the topic in focus. This helps in identifying key concepts to guide analysis and interpretation.

3. Collect the data

Case studies are frequently supplemented with qualitative data such as observations, interviews, and a review of both primary and secondary sources such as official records, news articles, and photographs. There may also be quantitative data —this data assists in understanding the case thoroughly.

4. Analyze your case

The results of the research depend on the research design. Most case studies are structured with chapters or topic headings for easy explanation and presentation. Others may be written as narratives to allow researchers to explore various angles of the topic and analyze its meanings and implications.

In all areas, always give a detailed contextual understanding of the case and connect it to the existing theory and literature before discussing how it fits into your problem area.

  • What are some case study examples?

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Case study of product marketing strategies in the Kenyan market

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How to use a case study in your masters dissertation

Prof martyn denscombe, author of “ the good research guide, 6th edition ”, gives expert advice on how to use a case study in your masters dissertation. .

There are two main examples for how to use a case study in your masters dissertation, namely quantitative and qualitative case studies.

First, a case study provides a platform that allows you to study a situation in depth and produce the level of academic inquiry that is expected in a master’s degree. In the context of any master’s programme the dissertation operates as something of a showcase for a student’s abilities.

It can easily make the difference between getting a merit and a distinction in the final award of degree. It is important, therefore, to base the work on an approach that allows things to be explored in sufficient depth and detail to warrant a good grade.

Second, case studies can be useful in a practical sense. It is possible to complete a case study in a relatively short period of intense study and so it is the kind of research that is feasible in terms of the kind of time constraints that face master’s students as they enter the final stages of their programme of study.

Added to which a case study can also be a rather convenient form of research, avoiding the time and costs of travel to multiple research sites. The use of case studies, then, would appear to be an attractive proposition. But it is not an approach that should be used naively without consideration of its limitations or potential pitfalls.

To be a good case study the research needs to consider certain key issues. If they are not addressed it will considerably lower the value of the master’s degree. For instance, a good case study needs to:

  • Be crystal clear about the purpose for which the research is being conducted
  • Justify the selection of the particular case being studied
  • Describe how the chosen case compares with others of its type
  • Explain the basis on which any generalizations can be made from the findings

This is where The Good Research Guide, 6th edition becomes so valuable. It not only identifies the key points that need to be addressed in order to conduct a competent questionnaire survey.

It gets right to the heart of the matter with plenty of practical guidance on how to deal with issues. Using plain language, this bestselling book covers a range of alternative strategies and methods for conducting small-scale social research projects. It outlines some of the main ways in which the data can be analysed.

Read Prof Martyn Denscombe’s advice on using a questionnaire survey for your postgraduate dissertation

Frequently Asked Questions

Can a case study be a thesis.

Yes, in fact a case study is a very good option in your dissertation. There are multiple ways to implement a case study in your thesis. For instance, one main study which is in depth and complex or you could feature multiple case studies.

What are case studies?

Case studies are a way to research a particular field, group, people and situation. The topic of research is studied deeply and thoroughly in order to solve a problem or uncover information. Case studies are a type of qualitative research.

If you are ready to find a masters course check out Masters Compare.

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The case study approach

Sarah crowe.

1 Division of Primary Care, The University of Nottingham, Nottingham, UK

Kathrin Cresswell

2 Centre for Population Health Sciences, The University of Edinburgh, Edinburgh, UK

Ann Robertson

3 School of Health in Social Science, The University of Edinburgh, Edinburgh, UK

Anthony Avery

Aziz sheikh.

The case study approach allows in-depth, multi-faceted explorations of complex issues in their real-life settings. The value of the case study approach is well recognised in the fields of business, law and policy, but somewhat less so in health services research. Based on our experiences of conducting several health-related case studies, we reflect on the different types of case study design, the specific research questions this approach can help answer, the data sources that tend to be used, and the particular advantages and disadvantages of employing this methodological approach. The paper concludes with key pointers to aid those designing and appraising proposals for conducting case study research, and a checklist to help readers assess the quality of case study reports.

Introduction

The case study approach is particularly useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context. Our aim in writing this piece is to provide insights into when to consider employing this approach and an overview of key methodological considerations in relation to the design, planning, analysis, interpretation and reporting of case studies.

The illustrative 'grand round', 'case report' and 'case series' have a long tradition in clinical practice and research. Presenting detailed critiques, typically of one or more patients, aims to provide insights into aspects of the clinical case and, in doing so, illustrate broader lessons that may be learnt. In research, the conceptually-related case study approach can be used, for example, to describe in detail a patient's episode of care, explore professional attitudes to and experiences of a new policy initiative or service development or more generally to 'investigate contemporary phenomena within its real-life context' [ 1 ]. Based on our experiences of conducting a range of case studies, we reflect on when to consider using this approach, discuss the key steps involved and illustrate, with examples, some of the practical challenges of attaining an in-depth understanding of a 'case' as an integrated whole. In keeping with previously published work, we acknowledge the importance of theory to underpin the design, selection, conduct and interpretation of case studies[ 2 ]. In so doing, we make passing reference to the different epistemological approaches used in case study research by key theoreticians and methodologists in this field of enquiry.

This paper is structured around the following main questions: What is a case study? What are case studies used for? How are case studies conducted? What are the potential pitfalls and how can these be avoided? We draw in particular on four of our own recently published examples of case studies (see Tables ​ Tables1, 1 , ​ ,2, 2 , ​ ,3 3 and ​ and4) 4 ) and those of others to illustrate our discussion[ 3 - 7 ].

Example of a case study investigating the reasons for differences in recruitment rates of minority ethnic people in asthma research[ 3 ]

Example of a case study investigating the process of planning and implementing a service in Primary Care Organisations[ 4 ]

Example of a case study investigating the introduction of the electronic health records[ 5 ]

Example of a case study investigating the formal and informal ways students learn about patient safety[ 6 ]

What is a case study?

A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table ​ (Table5), 5 ), the central tenet being the need to explore an event or phenomenon in depth and in its natural context. It is for this reason sometimes referred to as a "naturalistic" design; this is in contrast to an "experimental" design (such as a randomised controlled trial) in which the investigator seeks to exert control over and manipulate the variable(s) of interest.

Definitions of a case study

Stake's work has been particularly influential in defining the case study approach to scientific enquiry. He has helpfully characterised three main types of case study: intrinsic , instrumental and collective [ 8 ]. An intrinsic case study is typically undertaken to learn about a unique phenomenon. The researcher should define the uniqueness of the phenomenon, which distinguishes it from all others. In contrast, the instrumental case study uses a particular case (some of which may be better than others) to gain a broader appreciation of an issue or phenomenon. The collective case study involves studying multiple cases simultaneously or sequentially in an attempt to generate a still broader appreciation of a particular issue.

These are however not necessarily mutually exclusive categories. In the first of our examples (Table ​ (Table1), 1 ), we undertook an intrinsic case study to investigate the issue of recruitment of minority ethnic people into the specific context of asthma research studies, but it developed into a instrumental case study through seeking to understand the issue of recruitment of these marginalised populations more generally, generating a number of the findings that are potentially transferable to other disease contexts[ 3 ]. In contrast, the other three examples (see Tables ​ Tables2, 2 , ​ ,3 3 and ​ and4) 4 ) employed collective case study designs to study the introduction of workforce reconfiguration in primary care, the implementation of electronic health records into hospitals, and to understand the ways in which healthcare students learn about patient safety considerations[ 4 - 6 ]. Although our study focusing on the introduction of General Practitioners with Specialist Interests (Table ​ (Table2) 2 ) was explicitly collective in design (four contrasting primary care organisations were studied), is was also instrumental in that this particular professional group was studied as an exemplar of the more general phenomenon of workforce redesign[ 4 ].

What are case studies used for?

According to Yin, case studies can be used to explain, describe or explore events or phenomena in the everyday contexts in which they occur[ 1 ]. These can, for example, help to understand and explain causal links and pathways resulting from a new policy initiative or service development (see Tables ​ Tables2 2 and ​ and3, 3 , for example)[ 1 ]. In contrast to experimental designs, which seek to test a specific hypothesis through deliberately manipulating the environment (like, for example, in a randomised controlled trial giving a new drug to randomly selected individuals and then comparing outcomes with controls),[ 9 ] the case study approach lends itself well to capturing information on more explanatory ' how ', 'what' and ' why ' questions, such as ' how is the intervention being implemented and received on the ground?'. The case study approach can offer additional insights into what gaps exist in its delivery or why one implementation strategy might be chosen over another. This in turn can help develop or refine theory, as shown in our study of the teaching of patient safety in undergraduate curricula (Table ​ (Table4 4 )[ 6 , 10 ]. Key questions to consider when selecting the most appropriate study design are whether it is desirable or indeed possible to undertake a formal experimental investigation in which individuals and/or organisations are allocated to an intervention or control arm? Or whether the wish is to obtain a more naturalistic understanding of an issue? The former is ideally studied using a controlled experimental design, whereas the latter is more appropriately studied using a case study design.

Case studies may be approached in different ways depending on the epistemological standpoint of the researcher, that is, whether they take a critical (questioning one's own and others' assumptions), interpretivist (trying to understand individual and shared social meanings) or positivist approach (orientating towards the criteria of natural sciences, such as focusing on generalisability considerations) (Table ​ (Table6). 6 ). Whilst such a schema can be conceptually helpful, it may be appropriate to draw on more than one approach in any case study, particularly in the context of conducting health services research. Doolin has, for example, noted that in the context of undertaking interpretative case studies, researchers can usefully draw on a critical, reflective perspective which seeks to take into account the wider social and political environment that has shaped the case[ 11 ].

Example of epistemological approaches that may be used in case study research

How are case studies conducted?

Here, we focus on the main stages of research activity when planning and undertaking a case study; the crucial stages are: defining the case; selecting the case(s); collecting and analysing the data; interpreting data; and reporting the findings.

Defining the case

Carefully formulated research question(s), informed by the existing literature and a prior appreciation of the theoretical issues and setting(s), are all important in appropriately and succinctly defining the case[ 8 , 12 ]. Crucially, each case should have a pre-defined boundary which clarifies the nature and time period covered by the case study (i.e. its scope, beginning and end), the relevant social group, organisation or geographical area of interest to the investigator, the types of evidence to be collected, and the priorities for data collection and analysis (see Table ​ Table7 7 )[ 1 ]. A theory driven approach to defining the case may help generate knowledge that is potentially transferable to a range of clinical contexts and behaviours; using theory is also likely to result in a more informed appreciation of, for example, how and why interventions have succeeded or failed[ 13 ].

Example of a checklist for rating a case study proposal[ 8 ]

For example, in our evaluation of the introduction of electronic health records in English hospitals (Table ​ (Table3), 3 ), we defined our cases as the NHS Trusts that were receiving the new technology[ 5 ]. Our focus was on how the technology was being implemented. However, if the primary research interest had been on the social and organisational dimensions of implementation, we might have defined our case differently as a grouping of healthcare professionals (e.g. doctors and/or nurses). The precise beginning and end of the case may however prove difficult to define. Pursuing this same example, when does the process of implementation and adoption of an electronic health record system really begin or end? Such judgements will inevitably be influenced by a range of factors, including the research question, theory of interest, the scope and richness of the gathered data and the resources available to the research team.

Selecting the case(s)

The decision on how to select the case(s) to study is a very important one that merits some reflection. In an intrinsic case study, the case is selected on its own merits[ 8 ]. The case is selected not because it is representative of other cases, but because of its uniqueness, which is of genuine interest to the researchers. This was, for example, the case in our study of the recruitment of minority ethnic participants into asthma research (Table ​ (Table1) 1 ) as our earlier work had demonstrated the marginalisation of minority ethnic people with asthma, despite evidence of disproportionate asthma morbidity[ 14 , 15 ]. In another example of an intrinsic case study, Hellstrom et al.[ 16 ] studied an elderly married couple living with dementia to explore how dementia had impacted on their understanding of home, their everyday life and their relationships.

For an instrumental case study, selecting a "typical" case can work well[ 8 ]. In contrast to the intrinsic case study, the particular case which is chosen is of less importance than selecting a case that allows the researcher to investigate an issue or phenomenon. For example, in order to gain an understanding of doctors' responses to health policy initiatives, Som undertook an instrumental case study interviewing clinicians who had a range of responsibilities for clinical governance in one NHS acute hospital trust[ 17 ]. Sampling a "deviant" or "atypical" case may however prove even more informative, potentially enabling the researcher to identify causal processes, generate hypotheses and develop theory.

In collective or multiple case studies, a number of cases are carefully selected. This offers the advantage of allowing comparisons to be made across several cases and/or replication. Choosing a "typical" case may enable the findings to be generalised to theory (i.e. analytical generalisation) or to test theory by replicating the findings in a second or even a third case (i.e. replication logic)[ 1 ]. Yin suggests two or three literal replications (i.e. predicting similar results) if the theory is straightforward and five or more if the theory is more subtle. However, critics might argue that selecting 'cases' in this way is insufficiently reflexive and ill-suited to the complexities of contemporary healthcare organisations.

The selected case study site(s) should allow the research team access to the group of individuals, the organisation, the processes or whatever else constitutes the chosen unit of analysis for the study. Access is therefore a central consideration; the researcher needs to come to know the case study site(s) well and to work cooperatively with them. Selected cases need to be not only interesting but also hospitable to the inquiry [ 8 ] if they are to be informative and answer the research question(s). Case study sites may also be pre-selected for the researcher, with decisions being influenced by key stakeholders. For example, our selection of case study sites in the evaluation of the implementation and adoption of electronic health record systems (see Table ​ Table3) 3 ) was heavily influenced by NHS Connecting for Health, the government agency that was responsible for overseeing the National Programme for Information Technology (NPfIT)[ 5 ]. This prominent stakeholder had already selected the NHS sites (through a competitive bidding process) to be early adopters of the electronic health record systems and had negotiated contracts that detailed the deployment timelines.

It is also important to consider in advance the likely burden and risks associated with participation for those who (or the site(s) which) comprise the case study. Of particular importance is the obligation for the researcher to think through the ethical implications of the study (e.g. the risk of inadvertently breaching anonymity or confidentiality) and to ensure that potential participants/participating sites are provided with sufficient information to make an informed choice about joining the study. The outcome of providing this information might be that the emotive burden associated with participation, or the organisational disruption associated with supporting the fieldwork, is considered so high that the individuals or sites decide against participation.

In our example of evaluating implementations of electronic health record systems, given the restricted number of early adopter sites available to us, we sought purposively to select a diverse range of implementation cases among those that were available[ 5 ]. We chose a mixture of teaching, non-teaching and Foundation Trust hospitals, and examples of each of the three electronic health record systems procured centrally by the NPfIT. At one recruited site, it quickly became apparent that access was problematic because of competing demands on that organisation. Recognising the importance of full access and co-operative working for generating rich data, the research team decided not to pursue work at that site and instead to focus on other recruited sites.

Collecting the data

In order to develop a thorough understanding of the case, the case study approach usually involves the collection of multiple sources of evidence, using a range of quantitative (e.g. questionnaires, audits and analysis of routinely collected healthcare data) and more commonly qualitative techniques (e.g. interviews, focus groups and observations). The use of multiple sources of data (data triangulation) has been advocated as a way of increasing the internal validity of a study (i.e. the extent to which the method is appropriate to answer the research question)[ 8 , 18 - 21 ]. An underlying assumption is that data collected in different ways should lead to similar conclusions, and approaching the same issue from different angles can help develop a holistic picture of the phenomenon (Table ​ (Table2 2 )[ 4 ].

Brazier and colleagues used a mixed-methods case study approach to investigate the impact of a cancer care programme[ 22 ]. Here, quantitative measures were collected with questionnaires before, and five months after, the start of the intervention which did not yield any statistically significant results. Qualitative interviews with patients however helped provide an insight into potentially beneficial process-related aspects of the programme, such as greater, perceived patient involvement in care. The authors reported how this case study approach provided a number of contextual factors likely to influence the effectiveness of the intervention and which were not likely to have been obtained from quantitative methods alone.

In collective or multiple case studies, data collection needs to be flexible enough to allow a detailed description of each individual case to be developed (e.g. the nature of different cancer care programmes), before considering the emerging similarities and differences in cross-case comparisons (e.g. to explore why one programme is more effective than another). It is important that data sources from different cases are, where possible, broadly comparable for this purpose even though they may vary in nature and depth.

Analysing, interpreting and reporting case studies

Making sense and offering a coherent interpretation of the typically disparate sources of data (whether qualitative alone or together with quantitative) is far from straightforward. Repeated reviewing and sorting of the voluminous and detail-rich data are integral to the process of analysis. In collective case studies, it is helpful to analyse data relating to the individual component cases first, before making comparisons across cases. Attention needs to be paid to variations within each case and, where relevant, the relationship between different causes, effects and outcomes[ 23 ]. Data will need to be organised and coded to allow the key issues, both derived from the literature and emerging from the dataset, to be easily retrieved at a later stage. An initial coding frame can help capture these issues and can be applied systematically to the whole dataset with the aid of a qualitative data analysis software package.

The Framework approach is a practical approach, comprising of five stages (familiarisation; identifying a thematic framework; indexing; charting; mapping and interpretation) , to managing and analysing large datasets particularly if time is limited, as was the case in our study of recruitment of South Asians into asthma research (Table ​ (Table1 1 )[ 3 , 24 ]. Theoretical frameworks may also play an important role in integrating different sources of data and examining emerging themes. For example, we drew on a socio-technical framework to help explain the connections between different elements - technology; people; and the organisational settings within which they worked - in our study of the introduction of electronic health record systems (Table ​ (Table3 3 )[ 5 ]. Our study of patient safety in undergraduate curricula drew on an evaluation-based approach to design and analysis, which emphasised the importance of the academic, organisational and practice contexts through which students learn (Table ​ (Table4 4 )[ 6 ].

Case study findings can have implications both for theory development and theory testing. They may establish, strengthen or weaken historical explanations of a case and, in certain circumstances, allow theoretical (as opposed to statistical) generalisation beyond the particular cases studied[ 12 ]. These theoretical lenses should not, however, constitute a strait-jacket and the cases should not be "forced to fit" the particular theoretical framework that is being employed.

When reporting findings, it is important to provide the reader with enough contextual information to understand the processes that were followed and how the conclusions were reached. In a collective case study, researchers may choose to present the findings from individual cases separately before amalgamating across cases. Care must be taken to ensure the anonymity of both case sites and individual participants (if agreed in advance) by allocating appropriate codes or withholding descriptors. In the example given in Table ​ Table3, 3 , we decided against providing detailed information on the NHS sites and individual participants in order to avoid the risk of inadvertent disclosure of identities[ 5 , 25 ].

What are the potential pitfalls and how can these be avoided?

The case study approach is, as with all research, not without its limitations. When investigating the formal and informal ways undergraduate students learn about patient safety (Table ​ (Table4), 4 ), for example, we rapidly accumulated a large quantity of data. The volume of data, together with the time restrictions in place, impacted on the depth of analysis that was possible within the available resources. This highlights a more general point of the importance of avoiding the temptation to collect as much data as possible; adequate time also needs to be set aside for data analysis and interpretation of what are often highly complex datasets.

Case study research has sometimes been criticised for lacking scientific rigour and providing little basis for generalisation (i.e. producing findings that may be transferable to other settings)[ 1 ]. There are several ways to address these concerns, including: the use of theoretical sampling (i.e. drawing on a particular conceptual framework); respondent validation (i.e. participants checking emerging findings and the researcher's interpretation, and providing an opinion as to whether they feel these are accurate); and transparency throughout the research process (see Table ​ Table8 8 )[ 8 , 18 - 21 , 23 , 26 ]. Transparency can be achieved by describing in detail the steps involved in case selection, data collection, the reasons for the particular methods chosen, and the researcher's background and level of involvement (i.e. being explicit about how the researcher has influenced data collection and interpretation). Seeking potential, alternative explanations, and being explicit about how interpretations and conclusions were reached, help readers to judge the trustworthiness of the case study report. Stake provides a critique checklist for a case study report (Table ​ (Table9 9 )[ 8 ].

Potential pitfalls and mitigating actions when undertaking case study research

Stake's checklist for assessing the quality of a case study report[ 8 ]

Conclusions

The case study approach allows, amongst other things, critical events, interventions, policy developments and programme-based service reforms to be studied in detail in a real-life context. It should therefore be considered when an experimental design is either inappropriate to answer the research questions posed or impossible to undertake. Considering the frequency with which implementations of innovations are now taking place in healthcare settings and how well the case study approach lends itself to in-depth, complex health service research, we believe this approach should be more widely considered by researchers. Though inherently challenging, the research case study can, if carefully conceptualised and thoughtfully undertaken and reported, yield powerful insights into many important aspects of health and healthcare delivery.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

AS conceived this article. SC, KC and AR wrote this paper with GH, AA and AS all commenting on various drafts. SC and AS are guarantors.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2288/11/100/prepub

Acknowledgements

We are grateful to the participants and colleagues who contributed to the individual case studies that we have drawn on. This work received no direct funding, but it has been informed by projects funded by Asthma UK, the NHS Service Delivery Organisation, NHS Connecting for Health Evaluation Programme, and Patient Safety Research Portfolio. We would also like to thank the expert reviewers for their insightful and constructive feedback. Our thanks are also due to Dr. Allison Worth who commented on an earlier draft of this manuscript.

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Research Guides

Multiple Case Studies

Nadia Alqahtani and Pengtong Qu

Description

The case study approach is popular across disciplines in education, anthropology, sociology, psychology, medicine, law, and political science (Creswell, 2013). It is both a research method and a strategy (Creswell, 2013; Yin, 2017). In this type of research design, a case can be an individual, an event, or an entity, as determined by the research questions. There are two variants of the case study: the single-case study and the multiple-case study. The former design can be used to study and understand an unusual case, a critical case, a longitudinal case, or a revelatory case. On the other hand, a multiple-case study includes two or more cases or replications across the cases to investigate the same phenomena (Lewis-Beck, Bryman & Liao, 2003; Yin, 2017). …a multiple-case study includes two or more cases or replications across the cases to investigate the same phenomena

The difference between the single- and multiple-case study is the research design; however, they are within the same methodological framework (Yin, 2017). Multiple cases are selected so that “individual case studies either (a) predict similar results (a literal replication) or (b) predict contrasting results but for anticipatable reasons (a theoretical replication)” (p. 55). When the purpose of the study is to compare and replicate the findings, the multiple-case study produces more compelling evidence so that the study is considered more robust than the single-case study (Yin, 2017).

To write a multiple-case study, a summary of individual cases should be reported, and researchers need to draw cross-case conclusions and form a cross-case report (Yin, 2017). With evidence from multiple cases, researchers may have generalizable findings and develop theories (Lewis-Beck, Bryman & Liao, 2003).

Creswell, J. W. (2013). Qualitative inquiry and research design: Choosing among five approaches (3rd ed.). Los Angeles, CA: Sage.

Lewis-Beck, M., Bryman, A. E., & Liao, T. F. (2003). The Sage encyclopedia of social science research methods . Los Angeles, CA: Sage.

Yin, R. K. (2017). Case study research and applications: Design and methods . Los Angeles, CA: Sage.

Key Research Books and Articles on Multiple Case Study Methodology

Yin discusses how to decide if a case study should be used in research. Novice researchers can learn about research design, data collection, and data analysis of different types of case studies, as well as writing a case study report.

Chapter 2 introduces four major types of research design in case studies: holistic single-case design, embedded single-case design, holistic multiple-case design, and embedded multiple-case design. Novice researchers will learn about the definitions and characteristics of different designs. This chapter also teaches researchers how to examine and discuss the reliability and validity of the designs.

Creswell, J. W., & Poth, C. N. (2017). Qualitative inquiry and research design: Choosing among five approaches . Los Angeles, CA: Sage.

This book compares five different qualitative research designs: narrative research, phenomenology, grounded theory, ethnography, and case study. It compares the characteristics, data collection, data analysis and representation, validity, and writing-up procedures among five inquiry approaches using texts with tables. For each approach, the author introduced the definition, features, types, and procedures and contextualized these components in a study, which was conducted through the same method. Each chapter ends with a list of relevant readings of each inquiry approach.

This book invites readers to compare these five qualitative methods and see the value of each approach. Readers can consider which approach would serve for their research contexts and questions, as well as how to design their research and conduct the data analysis based on their choice of research method.

Günes, E., & Bahçivan, E. (2016). A multiple case study of preservice science teachers’ TPACK: Embedded in a comprehensive belief system. International Journal of Environmental and Science Education, 11 (15), 8040-8054.

In this article, the researchers showed the importance of using technological opportunities in improving the education process and how they enhanced the students’ learning in science education. The study examined the connection between “Technological Pedagogical Content Knowledge” (TPACK) and belief system in a science teaching context. The researchers used the multiple-case study to explore the effect of TPACK on the preservice science teachers’ (PST) beliefs on their TPACK level. The participants were three teachers with the low, medium, and high level of TPACK confidence. Content analysis was utilized to analyze the data, which were collected by individual semi-structured interviews with the participants about their lesson plans. The study first discussed each case, then compared features and relations across cases. The researchers found that there was a positive relationship between PST’s TPACK confidence and TPACK level; when PST had higher TPACK confidence, the participant had a higher competent TPACK level and vice versa.

Recent Dissertations Using Multiple Case Study Methodology

Milholland, E. S. (2015). A multiple case study of instructors utilizing Classroom Response Systems (CRS) to achieve pedagogical goals . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3706380)

The researcher of this study critiques the use of Classroom Responses Systems by five instructors who employed this program five years ago in their classrooms. The researcher conducted the multiple-case study methodology and categorized themes. He interviewed each instructor with questions about their initial pedagogical goals, the changes in pedagogy during teaching, and the teaching techniques individuals used while practicing the CRS. The researcher used the multiple-case study with five instructors. He found that all instructors changed their goals during employing CRS; they decided to reduce the time of lecturing and to spend more time engaging students in interactive activities. This study also demonstrated that CRS was useful for the instructors to achieve multiple learning goals; all the instructors provided examples of the positive aspect of implementing CRS in their classrooms.

Li, C. L. (2010). The emergence of fairy tale literacy: A multiple case study on promoting critical literacy of children through a juxtaposed reading of classic fairy tales and their contemporary disruptive variants . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3572104)

To explore how children’s development of critical literacy can be impacted by their reactions to fairy tales, the author conducted a multiple-case study with 4 cases, in which each child was a unit of analysis. Two Chinese immigrant children (a boy and a girl) and two American children (a boy and a girl) at the second or third grade were recruited in the study. The data were collected through interviews, discussions on fairy tales, and drawing pictures. The analysis was conducted within both individual cases and cross cases. Across four cases, the researcher found that the young children’s’ knowledge of traditional fairy tales was built upon mass-media based adaptations. The children believed that the representations on mass-media were the original stories, even though fairy tales are included in the elementary school curriculum. The author also found that introducing classic versions of fairy tales increased children’s knowledge in the genre’s origin, which would benefit their understanding of the genre. She argued that introducing fairy tales can be the first step to promote children’s development of critical literacy.

Asher, K. C. (2014). Mediating occupational socialization and occupational individuation in teacher education: A multiple case study of five elementary pre-service student teachers . Retrieved from ProQuest Dissertations & Theses Global. (Order Number 3671989)

This study portrayed five pre-service teachers’ teaching experience in their student teaching phase and explored how pre-service teachers mediate their occupational socialization with occupational individuation. The study used the multiple-case study design and recruited five pre-service teachers from a Midwestern university as five cases. Qualitative data were collected through interviews, classroom observations, and field notes. The author implemented the case study analysis and found five strategies that the participants used to mediate occupational socialization with occupational individuation. These strategies were: 1) hindering from practicing their beliefs, 2) mimicking the styles of supervising teachers, 3) teaching in the ways in alignment with school’s existing practice, 4) enacting their own ideas, and 5) integrating and balancing occupational socialization and occupational individuation. The study also provided recommendations and implications to policymakers and educators in teacher education so that pre-service teachers can be better supported.

Multiple Case Studies Copyright © 2019 by Nadia Alqahtani and Pengtong Qu is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Writing A Case Study

Types Of Case Study

Barbara P

Understand the Types of Case Study Here

Published on: Jun 22, 2019

Last updated on: Nov 29, 2023

Types of Case Study

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Case studies are effective research methods that focus on one specific case over time. This gives a detailed view that's great for learning.

Writing a case study is a very useful form of study in the educational process. With real-life examples, students can learn more effectively. 

A case study also has different types and forms. As a rule of thumb, all of them require a detailed and convincing answer based on a thorough analysis.

In this blog, we are going to discuss the different types of case study research methods in detail.

So, let’s dive right in!

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Understanding Case Studies

Case studies are a type of research methodology. Case study research designs examine subjects, projects, or organizations to provide an analysis based on the evidence.

It allows you to get insight into what causes any subject’s decisions and actions. This makes case studies a great way for students to develop their research skills.

A case study focuses on a single project for an extended period, which allows students to explore the topic in depth.

What are the Types of Case Study?

Multiple case studies are used for different purposes. The main purpose of case studies is to analyze problems within the boundaries of a specific organization, environment, or situation. 

Many aspects of a case study such as data collection and analysis, qualitative research questions, etc. are dependent on the researcher and what the study is looking to address. 

Case studies can be divided into the following categories:

Illustrative Case Study

Exploratory case study, cumulative case study, critical instance case study, descriptive case study, intrinsic case study, instrumental case study.

Let’s take a look at the detailed description of each type of case study with examples. 

An illustrative case study is used to examine a familiar case to help others understand it. It is one of the main types of case studies in research methodology and is primarily descriptive. 

In this type of case study, usually, one or two instances are used to explain what a situation is like. 

Here is an example to help you understand it better:

Illustrative Case Study Example

An exploratory case study is usually done before a larger-scale research. These types of case studies are very popular in the social sciences like political science and primarily focus on real-life contexts and situations.

This method is useful in identifying research questions and methods for a large and complex study. 

Let’s take a look at this example to help you have a better understanding:

Exploratory Case Study Example

A cumulative case study is one of the main types of case studies in qualitative research. It is used to collect information from different sources at different times.

This case study aims to summarize the past studies without spending additional cost and time on new investigations. 

Let’s take a look at the example below:

Cumulative Case Study Example

Critical instances case studies are used to determine the cause and consequence of an event. 

The main reason for this type of case study is to investigate one or more sources with unique interests and sometimes with no interest in general. 

Take a look at this example below:

Critical Instance Case Study Example

When you have a hypothesis, you can design a descriptive study. It aims to find connections between the subject being studied and a theory.

After making these connections, the study can be concluded. The results of the descriptive case study will usually suggest how to develop a theory further.

This example can help you understand the concept better:

Descriptive Case Study Example

Intrinsic studies are more commonly used in psychology, healthcare, or social work. So, if you were looking for types of case studies in sociology, or types of case studies in social research, this is it.

The focus of intrinsic studies is on the individual. The aim of such studies is not only to understand the subject better but also their history and how they interact with their environment.

Here is an example to help you understand;

Intrinsic Case Study Example

This type of case study is mostly used in qualitative research. In an instrumental case study, the specific case is selected to provide information about the research question.

It offers a lens through which researchers can explore complex concepts, theories, or generalizations.

Take a look at the example below to have a better understanding of the concepts:

Instrumental Case Study Example

Review some case study examples to help you understand how a specific case study is conducted.

Types of Subjects of Case Study 

In general, there are 5 types of subjects that case studies address. Every case study fits into the following subject categories. 

  • Person: This type of study focuses on one subject or individual and can use several research methods to determine the outcome. 
  • Group: This type of study takes into account a group of individuals. This could be a group of friends, coworkers, or family. 
  • Location: The main focus of this type of study is the place. It also takes into account how and why people use the place. 
  • Organization: This study focuses on an organization or company. This could also include the company employees or people who work in an event at the organization. 
  • Event: This type of study focuses on a specific event. It could be societal or cultural and examines how it affects the surroundings. 

Benefits of Case Study for Students

Here's a closer look at the multitude of benefits students can have with case studies:

Real-world Application

Case studies serve as a crucial link between theory and practice. By immersing themselves in real-world scenarios, students can apply theoretical knowledge to practical situations.

Critical Thinking Skills

Analyzing case studies demands critical thinking and informed decision-making. Students cultivate the ability to evaluate information, identify key factors, and develop well-reasoned solutions – essential skills in both academic and professional contexts.

Enhanced Problem-solving Abilities

Case studies often present complex problems that require creative and strategic solutions. Engaging with these challenges refines students' problem-solving skills, encouraging them to think innovatively and develop effective approaches.

Holistic Understanding

Going beyond theoretical concepts, case studies provide a holistic view of a subject. Students gain insights into the multifaceted aspects of a situation, helping them connect the dots and understand the broader context.

Exposure to Diverse Perspectives

Case studies often encompass a variety of industries, cultures, and situations. This exposure broadens students' perspectives, fostering a more comprehensive understanding of the world and the challenges faced by different entities.

So there you have it!

We have explored different types of case studies and their examples. Case studies act as the tools to understand and deal with the many challenges and opportunities around us.

Case studies are being used more and more in colleges and universities to help students understand how a hypothetical event can influence a person, group, or organization in real life. 

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Dr. Barbara is a highly experienced writer and author who holds a Ph.D. degree in public health from an Ivy League school. She has worked in the medical field for many years, conducting extensive research on various health topics. Her writing has been featured in several top-tier publications.

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Types of Case Study

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Frequently asked questions

What’s the difference between action research and a case study.

Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon.

Frequently asked questions: Methodology

Attrition refers to participants leaving a study. It always happens to some extent—for example, in randomized controlled trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

Action research is focused on solving a problem or informing individual and community-based knowledge in a way that impacts teaching, learning, and other related processes. It is less focused on contributing theoretical input, instead producing actionable input.

Action research is particularly popular with educators as a form of systematic inquiry because it prioritizes reflection and bridges the gap between theory and practice. Educators are able to simultaneously investigate an issue as they solve it, and the method is very iterative and flexible.

A cycle of inquiry is another name for action research . It is usually visualized in a spiral shape following a series of steps, such as “planning → acting → observing → reflecting.”

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

  • Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
  • Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

  • Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

Content validity shows you how accurately a test or other measurement method taps  into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analyzing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalizations —often the goal of quantitative research . As such, a snowball sample is not representative of the target population and is usually a better fit for qualitative research .

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones.

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is best used in the following cases:

  • If there is no sampling frame available (e.g., people with a rare disease)
  • If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
  • If the research focuses on a sensitive topic (e.g., extramarital affairs)

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Reproducibility and replicability are related terms.

  • Reproducing research entails reanalyzing the existing data in the same manner.
  • Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data . 
  • A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
  • A successful replication shows that the reliability of the results is high.

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Purposive and convenience sampling are both sampling methods that are typically used in qualitative data collection.

A convenience sample is drawn from a source that is conveniently accessible to the researcher. Convenience sampling does not distinguish characteristics among the participants. On the other hand, purposive sampling focuses on selecting participants possessing characteristics associated with the research study.

The findings of studies based on either convenience or purposive sampling can only be generalized to the (sub)population from which the sample is drawn, and not to the entire population.

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection, using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The key difference between observational studies and experimental designs is that a well-done observational study does not influence the responses of participants, while experiments do have some sort of treatment condition applied to at least some participants by random assignment .

An observational study is a great choice for you if your research question is based purely on observations. If there are ethical, logistical, or practical concerns that prevent you from conducting a traditional experiment , an observational study may be a good choice. In an observational study, there is no interference or manipulation of the research subjects, as well as no control or treatment groups .

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity ,  because it covers all of the other types. You need to have face validity , content validity , and criterion validity to achieve construct validity.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

  • Convergent validity : The extent to which your measure corresponds to measures of related constructs
  • Discriminant validity : The extent to which your measure is unrelated or negatively related to measures of distinct constructs

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

Naturalistic observation is a qualitative research method where you record the behaviors of your research subjects in real world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as “people watching” with a purpose.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it “depends” on your independent variable.

In statistics, dependent variables are also called:

  • Response variables (they respond to a change in another variable)
  • Outcome variables (they represent the outcome you want to measure)
  • Left-hand-side variables (they appear on the left-hand side of a regression equation)

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called “independent” because it’s not influenced by any other variables in the study.

Independent variables are also called:

  • Explanatory variables (they explain an event or outcome)
  • Predictor variables (they can be used to predict the value of a dependent variable)
  • Right-hand-side variables (they appear on the right-hand side of a regression equation).

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups. Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

  • Open-ended and flexible
  • Impossible to answer with “yes” or “no” (questions that start with “why” or “how” are often best)
  • Unambiguous, getting straight to the point while still stimulating discussion
  • Unbiased and neutral

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when: 

  • You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
  • You are constrained in terms of time or resources and need to analyze your data quickly and efficiently.
  • Your research question depends on strong parity between participants, with environmental conditions held constant.

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias is the tendency for interview participants to give responses that will be viewed favorably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias can also occur in observations if the participants know they’re being observed. They might alter their behavior accordingly.

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

  • You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
  • Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

  • You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions.
  • Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
  • You are seeking descriptive data, and are ready to ask questions that will deepen and contextualize your initial thoughts and hypotheses.
  • Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts.

The four most common types of interviews are:

  • Structured interviews : The questions are predetermined in both topic and order. 
  • Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
  • Unstructured interviews : None of the questions are predetermined.
  • Focus group interviews : The questions are presented to a group instead of one individual.

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

  • Inductive generalization : You use observations about a sample to come to a conclusion about the population it came from.
  • Statistical generalization: You use specific numbers about samples to make statements about populations.
  • Causal reasoning: You make cause-and-effect links between different things.
  • Sign reasoning: You make a conclusion about a correlational relationship between different things.
  • Analogical reasoning: You make a conclusion about something based on its similarities to something else.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess — it should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations and statistical analysis of data).

Triangulation can help:

  • Reduce research bias that comes from using a single method, theory, or investigator
  • Enhance validity by approaching the same topic with different tools
  • Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

  • It’s time-consuming and labor-intensive, often involving an interdisciplinary team.
  • Your results may be inconsistent or even contradictory.

There are four main types of triangulation :

  • Data triangulation : Using data from different times, spaces, and people
  • Investigator triangulation : Involving multiple researchers in collecting or analyzing data
  • Theory triangulation : Using varying theoretical perspectives in your research
  • Methodological triangulation : Using different methodologies to approach the same topic

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure. 

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field. It acts as a first defense, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps: 

  • First, the author submits the manuscript to the editor.
  • Reject the manuscript and send it back to author, or 
  • Send it onward to the selected peer reviewer(s) 
  • Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made. 
  • Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Exploratory research aims to explore the main aspects of an under-researched problem, while explanatory research aims to explain the causes and consequences of a well-defined problem.

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardization and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Every dataset requires different techniques to clean dirty data , but you need to address these issues in a systematic way. You focus on finding and resolving data points that don’t agree or fit with the rest of your dataset.

These data might be missing values, outliers, duplicate values, incorrectly formatted, or irrelevant. You’ll start with screening and diagnosing your data. Then, you’ll often standardize and accept or remove data to make your dataset consistent and valid.

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimize or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyze, detect, modify, or remove “dirty” data to make your dataset “clean.” Data cleaning is also called data cleansing or data scrubbing.

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information—for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

In multistage sampling , you can use probability or non-probability sampling methods .

For a probability sample, you have to conduct probability sampling at every stage.

You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

These are four of the most common mixed methods designs :

  • Convergent parallel: Quantitative and qualitative data are collected at the same time and analyzed separately. After both analyses are complete, compare your results to draw overall conclusions. 
  • Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
  • Explanatory sequential: Quantitative data is collected and analyzed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualize your quantitative findings.
  • Exploratory sequential: Qualitative data is collected and analyzed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from state to city to neighborhood) to create a sample that’s less expensive and time-consuming to collect data from.

No, the steepness or slope of the line isn’t related to the correlation coefficient value. The correlation coefficient only tells you how closely your data fit on a line, so two datasets with the same correlation coefficient can have very different slopes.

To find the slope of the line, you’ll need to perform a regression analysis .

Correlation coefficients always range between -1 and 1.

The sign of the coefficient tells you the direction of the relationship: a positive value means the variables change together in the same direction, while a negative value means they change together in opposite directions.

The absolute value of a number is equal to the number without its sign. The absolute value of a correlation coefficient tells you the magnitude of the correlation: the greater the absolute value, the stronger the correlation.

These are the assumptions your data must meet if you want to use Pearson’s r :

  • Both variables are on an interval or ratio level of measurement
  • Data from both variables follow normal distributions
  • Your data have no outliers
  • Your data is from a random or representative sample
  • You expect a linear relationship between the two variables

Quantitative research designs can be divided into two main categories:

  • Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
  • Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

The priorities of a research design can vary depending on the field, but you usually have to specify:

  • Your research questions and/or hypotheses
  • Your overall approach (e.g., qualitative or quantitative )
  • The type of design you’re using (e.g., a survey , experiment , or case study )
  • Your sampling methods or criteria for selecting subjects
  • Your data collection methods (e.g., questionnaires , observations)
  • Your data collection procedures (e.g., operationalization , timing and data management)
  • Your data analysis methods (e.g., statistical tests  or thematic analysis )

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or through mail. All questions are standardized so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in-person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

You can organize the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomization can minimize the bias from order effects.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analyzing data from people using questionnaires.

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

Correlation describes an association between variables : when one variable changes, so does the other. A correlation is a statistical indicator of the relationship between variables.

Causation means that changes in one variable brings about changes in the other (i.e., there is a cause-and-effect relationship between variables). The two variables are correlated with each other, and there’s also a causal link between them.

While causation and correlation can exist simultaneously, correlation does not imply causation. In other words, correlation is simply a relationship where A relates to B—but A doesn’t necessarily cause B to happen (or vice versa). Mistaking correlation for causation is a common error and can lead to false cause fallacy .

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

  • In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
  • In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation reflects the strength and/or direction of the association between two or more variables.

  • A positive correlation means that both variables change in the same direction.
  • A negative correlation means that the variables change in opposite directions.
  • A zero correlation means there’s no relationship between the variables.

Random error  is almost always present in scientific studies, even in highly controlled settings. While you can’t eradicate it completely, you can reduce random error by taking repeated measurements, using a large sample, and controlling extraneous variables .

You can avoid systematic error through careful design of your sampling , data collection , and analysis procedures. For example, use triangulation to measure your variables using multiple methods; regularly calibrate instruments or procedures; use random sampling and random assignment ; and apply masking (blinding) where possible.

Systematic error is generally a bigger problem in research.

With random error, multiple measurements will tend to cluster around the true value. When you’re collecting data from a large sample , the errors in different directions will cancel each other out.

Systematic errors are much more problematic because they can skew your data away from the true value. This can lead you to false conclusions ( Type I and II errors ) about the relationship between the variables you’re studying.

Random and systematic error are two types of measurement error.

Random error is a chance difference between the observed and true values of something (e.g., a researcher misreading a weighing scale records an incorrect measurement).

Systematic error is a consistent or proportional difference between the observed and true values of something (e.g., a miscalibrated scale consistently records weights as higher than they actually are).

On graphs, the explanatory variable is conventionally placed on the x-axis, while the response variable is placed on the y-axis.

  • If you have quantitative variables , use a scatterplot or a line graph.
  • If your response variable is categorical, use a scatterplot or a line graph.
  • If your explanatory variable is categorical, use a bar graph.

The term “ explanatory variable ” is sometimes preferred over “ independent variable ” because, in real world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so “explanatory variables” is a more appropriate term.

The difference between explanatory and response variables is simple:

  • An explanatory variable is the expected cause, and it explains the results.
  • A response variable is the expected effect, and it responds to other variables.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

  • A control group that receives a standard treatment, a fake treatment, or no treatment.
  • Random assignment of participants to ensure the groups are equivalent.

Depending on your study topic, there are various other methods of controlling variables .

There are 4 main types of extraneous variables :

  • Demand characteristics : environmental cues that encourage participants to conform to researchers’ expectations.
  • Experimenter effects : unintentional actions by researchers that influence study outcomes.
  • Situational variables : environmental variables that alter participants’ behaviors.
  • Participant variables : any characteristic or aspect of a participant’s background that could affect study results.

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

Advantages:

  • Only requires small samples
  • Statistically powerful
  • Removes the effects of individual differences on the outcomes

Disadvantages:

  • Internal validity threats reduce the likelihood of establishing a direct relationship between variables
  • Time-related effects, such as growth, can influence the outcomes
  • Carryover effects mean that the specific order of different treatments affect the outcomes

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

  • Prevents carryover effects of learning and fatigue.
  • Shorter study duration.
  • Needs larger samples for high power.
  • Uses more resources to recruit participants, administer sessions, cover costs, etc.
  • Individual differences may be an alternative explanation for results.

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word “between” means that you’re comparing different conditions between groups, while the word “within” means you’re comparing different conditions within the same group.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a dice to randomly assign participants to groups.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalizability of your results, while random assignment improves the internal validity of your study.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomization. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

“Controlling for a variable” means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

If something is a mediating variable :

  • It’s caused by the independent variable .
  • It influences the dependent variable
  • When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered.

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

There are three key steps in systematic sampling :

  • Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
  • Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
  • Choose every k th member of the population as your sample.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 x 5 = 15 subgroups.

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

  • In single-stage sampling , you collect data from every unit within the selected clusters.
  • In double-stage sampling , you select a random sample of units from within the clusters.
  • In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

The American Community Survey  is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data is then collected from as large a percentage as possible of this random subset.

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity  as they can use real-world interventions instead of artificial laboratory settings.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference with a true experiment is that the groups are not randomly assigned.

Blinding is important to reduce research bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behavior in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

  • In a single-blind study , only the participants are blinded.
  • In a double-blind study , both participants and experimenters are blinded.
  • In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analyzing the data.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

A true experiment (a.k.a. a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyze your data.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviors. It is made up of 4 or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with 5 or 7 possible responses, to capture their degree of agreement.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalization .

There are various approaches to qualitative data analysis , but they all share five steps in common:

  • Prepare and organize your data.
  • Review and explore your data.
  • Develop a data coding system.
  • Assign codes to the data.
  • Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

There are five common approaches to qualitative research :

  • Grounded theory involves collecting data in order to develop new theories.
  • Ethnography involves immersing yourself in a group or organization to understand its culture.
  • Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
  • Phenomenological research involves investigating phenomena through people’s lived experiences.
  • Action research links theory and practice in several cycles to drive innovative changes.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

When conducting research, collecting original data has significant advantages:

  • You can tailor data collection to your specific research aims (e.g. understanding the needs of your consumers or user testing your website)
  • You can control and standardize the process for high reliability and validity (e.g. choosing appropriate measurements and sampling methods )

However, there are also some drawbacks: data collection can be time-consuming, labor-intensive and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomization , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both!

You want to find out how blood sugar levels are affected by drinking diet soda and regular soda, so you conduct an experiment .

  • The type of soda – diet or regular – is the independent variable .
  • The level of blood sugar that you measure is the dependent variable – it changes depending on the type of soda.

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling, and quota sampling .

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

Using careful research design and sampling procedures can help you avoid sampling bias . Oversampling can be used to correct undercoverage bias .

Some common types of sampling bias include self-selection bias , nonresponse bias , undercoverage bias , survivorship bias , pre-screening or advertising bias, and healthy user bias.

Sampling bias is a threat to external validity – it limits the generalizability of your findings to a broader group of people.

A sampling error is the difference between a population parameter and a sample statistic .

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment and situation effect.

The two types of external validity are population validity (whether you can generalize to other groups of people) and ecological validity (whether you can generalize to other situations and settings).

The external validity of a study is the extent to which you can generalize your findings to different groups of people, situations, and measures.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyze behavior over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data is available for analysis; other times your research question may only require a cross-sectional study to answer it.

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction and attrition .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

The research methods you use depend on the type of data you need to answer your research question .

  • If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts and meanings, use qualitative methods .
  • If you want to analyze a large amount of readily-available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data.
  • If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

Discrete and continuous variables are two types of quantitative variables :

  • Discrete variables represent counts (e.g. the number of objects in a collection).
  • Continuous variables represent measurable amounts (e.g. water volume or weight).

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

  • The  independent variable  is the amount of nutrients added to the crop field.
  • The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Experimental design means planning a set of procedures to investigate a relationship between variables . To design a controlled experiment, you need:

  • A testable hypothesis
  • At least one independent variable that can be precisely manipulated
  • At least one dependent variable that can be precisely measured

When designing the experiment, you decide:

  • How you will manipulate the variable(s)
  • How you will control for any potential confounding variables
  • How many subjects or samples will be included in the study
  • How subjects will be assigned to treatment levels

Experimental design is essential to the internal and external validity of your experiment.

I nternal validity is the degree of confidence that the causal relationship you are testing is not influenced by other factors or variables .

External validity is the extent to which your results can be generalized to other contexts.

The validity of your experiment depends on your experimental design .

Reliability and validity are both about how well a method measures something:

  • Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
  • Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research, you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population . Sampling means selecting the group that you will actually collect data from in your research. For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyze data (for example, experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

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Case Study Thesis Statement Examples, How to Write, Tips

Case Study Thesis Statement Examples

A case study is a deep and comprehensive study of a specific subject, such as individuals, groups, or events, in their real-life context. Crafting a compelling thesis statement for a case study ensures that readers are primed to engage with the detailed analysis that follows. It sets the tone and provides a roadmap for what’s to be explored. Whether you’re examining a business scenario, a societal issue, or a psychological condition, a well-constructed thesis sets the foundation. Let’s delve into examples, writing techniques, and tips to perfect this art.

What is a Case Study Thesis Statement? – Definition

A case study thesis statement is a concise summary that outlines the central point or argument of a case study. It encapsulates the primary findings, insights, or conclusions drawn from the detailed analysis of a particular subject or situation in its real-life context. This statement serves as a guide for readers, offering a snapshot of what the case study will explore and the significance of its findings.

What is an example of a Case Study thesis statement?

“In the analysis of XYZ Corporation’s marketing strategies during the fiscal year 2020-2021, it’s evident that the company’s innovative use of social media advertising not only boosted its brand visibility among millennials but also led to a 15% increase in sales, demonstrating the power of digital platforms in modern business models.”

This Specific thesis statement provides a clear insight into the focus of the case study (XYZ Corporation’s marketing strategies) and highlights the primary conclusion (success in using social media advertising to boost sales).

100 Case Study Thesis Statement Examples

case study thesis statement examples

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Case study thesis statements provide a concise encapsulation of the primary conclusions or insights gleaned from an in-depth analysis of a subject. They serve as a roadmap for readers, informing them of the study’s focal points and key findings. To craft an effective case study thesis, it’s imperative to be specific, evidence-based, and relevant to the subject being explored. Below are 100 examples spanning various fields and scenarios:

  • Analyzing the success of Apple’s iPhone X launch, it’s evident that the blend of technological innovation and targeted marketing resulted in record-breaking sales figures globally.
  • A deep dive into London’s urban planning post-2000 reveals a significant push towards sustainable infrastructure, reducing the city’s carbon footprint by 12%.
  • In studying patient recovery rates at the ABC Rehabilitation Center, it becomes clear that personalized therapy programs yield a 25% faster recovery time compared to generic methods.
  • A review of Brazil’s reforestation efforts in the last decade demonstrates that community involvement is a pivotal factor, with local engagement accelerating afforestation by 18%.
  • Exploring the financial collapse of Company XYZ in 2019, mismanagement of funds and a lack of internal audits were the predominant causes leading to its bankruptcy.
  • The rise in mental health issues among high school students from 2015-2020, as examined in Region A, strongly correlates with increased social media usage and cyberbullying incidents.
  • A detailed analysis of Japan’s public transport system reveals that timely investments in technology and maintenance are primary reasons for its 99% punctuality rate.
  • Studying the diet patterns of Mediterranean regions provides insights into lower cardiovascular disease rates, highlighting the benefits of olive oil, fish, and whole grains.
  • The decline in print media sales from 2000-2020, as evident in the case of Magazine ABC, is largely due to the surge in digital content consumption and changing reader habits.
  • In assessing the success of the ‘Clean River’ campaign in City B, it’s observed that public awareness drives and stricter industrial regulations reduced water pollution by 30%
  • An examination of solar energy adoption in Rural Region X indicates that governmental subsidies coupled with community workshops played a pivotal role in increasing installations by 40% in five years.
  • By delving into the cultural revival in City Y, it’s apparent that grassroots movements and local art festivals were instrumental in rejuvenating traditional art forms and bolstering tourism.
  • A study of telecommuting trends during the 2020 pandemic reveals that companies with pre-existing digital infrastructure reported a smoother transition and a mere 5% drop in productivity.
  • Through analyzing the public health response in Country Z during the measles outbreak, it’s clear that rapid immunization drives and public awareness campaigns curbed the spread by 60%.
  • A review of the organic farming movement in Region P shows that farmer cooperatives and government-backed training sessions were crucial in tripling organic produce output in a decade.
  • Assessing the success factors behind Brand Q’s viral ad campaign, a blend of humor, social relevance, and effective online targeting resulted in a 300% ROI.
  • An in-depth look at the urban wildlife conservation initiative in City R suggests that integrating green corridors and public education were key to increasing urban biodiversity by 20%.
  • Studying the economic turnaround of City S post-recession, it emerges that a combination of SME incentives, infrastructure investments, and tourism promotions led to a steady 7% GDP growth.
  • Exploring the education overhaul in District T, the introduction of experiential learning methods and teacher training programs significantly improved student performance metrics across all grades.
  • The analysis of e-commerce trends in Country U during the festive season underscores that localized marketing campaigns and easy return policies boosted sales by an unprecedented 45%
  • An exploration of the rehabilitation programs in Prison V reveals that the integration of vocational training reduced recidivism rates by 15% over three years.
  • Investigating the decline of traditional crafts in Region W, it becomes apparent that globalized market pressures and a generational shift in career preferences were primary contributors.
  • The analysis of startup ecosystem growth in City X demonstrates that mentorship programs and venture capital accessibility were crucial drivers, leading to a 50% increase in successful startup launches.
  • In evaluating the healthcare system of Country Y, the strategic placement of clinics and telemedicine integration were central to achieving a 90% accessibility rate in remote areas.
  • Studying the architectural evolution in City Z, the emphasis on eco-friendly designs and green spaces has significantly enhanced residents’ quality of life and reduced energy consumption.
  • A detailed assessment of the digital literacy program in District A1 indicates that hands-on workshops and collaboration with tech companies led to a 30% increase in digital skills among the elderly.
  • The case study of the MNO Music Festival shows that blending international and local artists, along with immersive cultural experiences, resulted in a tripling of international attendees.
  • In examining the rebranding strategy of Company B2, leveraging user-generated content and transparency in production processes garnered a 60% boost in brand loyalty.
  • Exploring the impact of the ‘Green School’ initiative in Region C3, schools that integrated environmental education witnessed a marked increase in student-led sustainability projects.
  • By delving into the tourism dynamics of Island D4, it’s observed that the emphasis on eco-tourism and cultural preservation led to sustained tourism growth without ecological degradation.
  • A deep dive into the public transport upgrades in City E5 reveals that the inclusion of smart ticketing systems and real-time tracking improved user satisfaction rates by 25%.
  • Analyzing the performance of the XYZ sports team over a decade, the focus on grassroots talent recruitment and continuous training regimes was key to their championship victories.
  • A study of the fast-food industry shifts in Region F6 showcases that the introduction of plant-based menu options was instrumental in capturing a new health-conscious demographic.
  • Through assessing the cybersecurity reforms in Organization G7, proactive threat monitoring and employee training drastically reduced security breaches by 80%.
  • An examination of the ‘Urban Forest’ project in City H8 underlines that community participation and periodic maintenance drives ensured a 90% survival rate of planted trees.
  • Investigating the cultural festival in Village I9, the collaboration with local artisans and digital promotions drew an unprecedented global audience, revitalizing the local economy
  • The scrutiny of e-learning trends in School J10 revealed that blending video tutorials with interactive assignments resulted in higher student engagement and a 20% improvement in test scores.
  • In studying the revamp of the K11 shopping mall, the introduction of experiential retail spaces and diversified dining options significantly increased footfall and monthly sales.
  • By analyzing the success of the L12 mobile banking app, user-friendly interfaces combined with robust security measures led to a user adoption rate surpassing 70% within the first year.
  • The comprehensive review of NGO M13’s outreach programs indicates that localized content and leveraging social media influencers amplified awareness, doubling donations received.
  • An in-depth study of the transportation overhaul in City N14 highlights that integrating cycling lanes and pedestrian zones reduced vehicular traffic by 15% and enhanced urban livability.
  • A case study on the O15 biotech startup’s rapid growth identifies that collaborations with academic institutions and a focus on sustainable solutions were critical success factors.
  • Investigating the wildlife conservation measures in Park P16, the integration of community-based surveillance and eco-tourism initiatives resulted in a 10% rise in endangered species populations.
  • Exploring the dynamics of the Q17 film festival, the embrace of indie filmmakers and diversification into virtual screenings expanded the global audience base by threefold.
  • Through a detailed assessment of the R18 smart city project, data-driven decision-making and public-private partnerships accelerated infrastructure development and improved resident satisfaction.
  • A study of the resurgence of traditional crafts in Village S19 underscores that governmental grants combined with e-commerce platforms enabled artisans to reach global markets and triple their income.
  • By analyzing the mental health initiative in University T20, the introduction of peer counseling and mindfulness workshops led to a 30% decrease in reported student stress levels.
  • In evaluating the U21 sustainable farming project, the practice of crop rotation and organic pest control methods doubled yields without compromising soil health.
  • A deep dive into the V22 robotics industry shows that investments in research and development, coupled with industry-academia partnerships, positioned the region as a global leader in automation solutions.
  • The case study of the W23 urban renewal initiative reveals that preserving historical sites while integrating modern amenities revitalized the district and boosted tourism by 40%
  • Exploring the telehealth revolution in Hospital X24, it’s evident that user-centric design coupled with real-time patient support drastically reduced waiting times and enhanced patient satisfaction.
  • A review of the Z25 green tech startup’s rise showcases how tapping into emerging markets and prioritizing local adaptations enabled a 250% growth rate over two years.
  • By analyzing the Y26 literary festival’s global success, forging partnerships with international publishers and leveraging livestreamed sessions captured a diversified and engaged global readership.
  • In evaluating the urban art projects of City A27, integrating community artists and sourcing local materials led to culturally resonant artworks and rejuvenated public spaces.
  • The detailed study of B28’s freshwater conservation strategies highlights that community education, combined with sustainable fishing practices, restored marine life balance within a decade.
  • Through a comprehensive look at the C29 space tech firm’s accomplishments, early investments in satellite miniaturization positioned it as a front-runner in commercial space solutions.
  • By delving into the digital transformation of Retailer D30, the integration of augmented reality for virtual try-ons significantly boosted online sales and reduced return rates.
  • A study of the E31 desert afforestation initiative reveals that harnessing native drought-resistant flora and community-based irrigation systems successfully greened over 10,000 hectares.
  • Exploring F32’s inclusive education reforms, a curriculum designed with multi-modal teaching techniques led to improved learning outcomes for differently-abled students.
  • In examining the eco-tourism drive of Island G33, maintaining a balance between visitor volume and ecological sustainability ensured steady revenue without environmental degradation.
  • Analyzing the H34 online gaming platform’s surge in popularity, community engagement features and regional game localization were instrumental in its global user base expansion.
  • A review of the I35 urban cycling initiative shows that creating cyclist-friendly infrastructure, coupled with public awareness campaigns, led to a 20% increase in daily cycling commuters.
  • In studying J36’s public library modernization project, the fusion of digital archives with interactive learning zones increased visitor numbers and enhanced community learning.
  • By evaluating the K37 corporate wellness program, a holistic approach encompassing mental health, fitness, and nutrition resulted in a 15% reduction in employee sick days.
  • A detailed look at the L38 organic coffee farming cooperative identifies that fair-trade certifications and eco-friendly processing techniques doubled farmer profits and market reach.
  • Exploring the M39 microfinance model in developing regions shows that leveraging mobile technology and community leaders made financial services accessible to previously unbanked populations.
  • The case study of N40’s anti-pollution drive reveals that using technology for real-time air quality monitoring and public alerts led to actionable civic interventions and clearer skies.
  • Analyzing the O41 cultural dance revival initiative, collaborations with schools and televised events reintroduced traditional dances to younger generations, preserving cultural heritage.
  • Through studying the P42 renewable energy project, community-owned solar and wind farms not only achieved energy self-sufficiency but also created local employment opportunities.
  • By examining Q43’s digital archival project, crowdsourcing contributions and integrating multimedia storytelling resurrected historical narratives for a global digital audience.
  • In reviewing the R44 disaster response initiative, utilizing drones and AI-driven analytics for real-time situation assessment led to a 30% faster rescue response.
  • Exploring the success of the S45 women’s empowerment project, localized workshops and financial literacy programs led to the establishment of over 500 women-led businesses.
  • Analyzing the T46 urban farming revolution, rooftop gardens and vertical farming technologies not only reduced the carbon footprint but also bolstered local food security.
  • Through a detailed examination of U47’s mental health awareness campaign, leveraging celebrity ambassadors and social media channels destigmatized mental health discussions among young adults.
  • The study of V48’s coastal conservation initiative reveals that coral transplantation and sustainable tourism practices significantly enhanced marine biodiversity and local livelihoods.
  • By scrutinizing the W49 digital arts program, collaborations with global tech firms and virtual exhibitions brought contemporary art to a wider and more diversified audience.
  • In evaluating the X50 grassroots sports initiative, talent scouting at school levels and offering specialized training camps led to a surge in regional sports achievements.
  • Exploring the Y51 urban greenery project, the symbiotic integration of flora with urban structures, like bus stops and building facades, transformed the cityscape and improved air quality.
  • Through analyzing the Z52 elderly wellness initiative, mobile health check-ups and community gathering events significantly improved the well-being and social connectedness of seniors.
  • A deep dive into A53’s tech literacy drive for rural regions showcases that mobile classrooms and gamified learning tools bridged the digital divide, empowering communities.
  • Investigating B54’s smart waste management project, sensor-fitted bins and data-driven route optimization for collection trucks minimized operational costs and improved city cleanliness.
  • The case study of C55’s heritage restoration initiative highlights that a blend of traditional craftsmanship with modern conservation techniques revitalized historical landmarks, boosting tourism.
  • In studying D56’s alternative education model, experiential outdoor learning and community projects fostered holistic student development and real-world problem-solving skills.
  • By analyzing E57’s urban transit solution, electric buses paired with dynamic route algorithms resulted in reduced traffic congestion and a decrease in emissions.
  • The examination of F58’s sustainable fashion movement indicates that upcycling workshops and eco-conscious designer collaborations led to a greener fashion industry with reduced waste.
  • Through a deep dive into G59’s wildlife rehabilitation project, mobile veterinary units and habitat restoration measures significantly increased the population of endangered species.
  • In assessing H60’s collaborative workspace model, creating modular designs and fostering community events led to increased startup incubation and knowledge exchange.
  • Studying the I61 teletherapy initiative, the integration of wearable tech for biometric feedback and real-time counseling support made mental health care more accessible and tailored.
  • The review of J62’s community theater resurgence underlines that offering free training workshops and forging school partnerships enriched cultural landscapes and nurtured local talent.
  • By evaluating K63’s clean water initiative in remote areas, solar-powered desalination units and community-led maintenance ensured uninterrupted access to potable water.
  • Exploring the L64 sustainable architecture movement, it’s evident that the incorporation of passive solar design and green roofs reduced building energy consumption by up to 40%.
  • Through a detailed analysis of the M65 virtual reality (VR) in education program, integrating VR expeditions and interactive simulations led to a 20% increase in student comprehension.
  • The study of N66’s eco-village development project reveals that community-owned renewable energy systems and permaculture designs fostered self-sufficiency and resilience.
  • By reviewing the O67’s inclusive playground initiative, universally designed play equipment and sensory-friendly zones catered to children of all abilities, promoting inclusivity and joy.
  • Investigating the P68’s digital heritage preservation, utilizing 3D scanning and augmented reality brought ancient monuments and artifacts to life for global audiences.
  • By scrutinizing the Q69’s local organic produce movement, direct farmer-to-consumer platforms and community-supported agriculture initiatives revitalized local economies and promoted healthy living.
  • A deep dive into the R70’s urban beekeeping project indicates that rooftop apiaries and bee-friendly green spaces boosted pollinator populations, benefiting both biodiversity and urban agriculture.
  • In evaluating the S71’s community radio station initiative, platforms that prioritized local news and indigenous languages fostered civic participation and cultural pride.
  • Exploring the success of T72’s renewable energy transition, investments in grid-tied wind and solar farms led to the region achieving carbon neutrality within a decade.
  • The review of U73’s zero-waste community challenge highlights that community workshops on composting, recycling, and upcycling drastically reduced landfill contributions and elevated environmental consciousness.

These statements encompass a diverse range of endeavors, from technological innovations and educational transformations to environmental conservation and cultural preservation. Each thesis offers a concise yet compelling entry point, illustrating the multifaceted nature of case studies and their potential to drive change across various sectors.

Case Study Thesis Statement Example for Argumentative Essay

An argumentative essay’s thesis statement presents a debatable claim about a particular scenario or situation, seeking to persuade the reader of its validity. It combines evidence from the case study with a clear stance on the matter, aiming to convince through both factual data and logical reasoning.

  • Despite the surge in e-commerce, a case study on Brick & Mortar Retail Y1 reveals that experiential in-store shopping can significantly boost customer loyalty and overall sales.
  • Examining the X2 city’s public transport model, it’s evident that prioritizing bicycles over cars results in healthier urban environments and happier citizens.
  • By studying vegan diets through the Z3 health initiative, there is undeniable evidence that plant-based diets lead to improved overall health metrics when compared to omnivorous diets.
  • Through a deep dive into the A4’s shift to remote work, productivity levels and employee well-being evidently increase when offered flexible work arrangements.
  • In the debate over renewable versus fossil fuels, the B5 country’s successful transition showcases the undeniable economic and environmental advantages of renewable energy.
  • Analyzing the C6 city’s urban greening project, it’s clear that community gardens play a pivotal role in crime reduction and social cohesion.
  • A study on the D7’s educational reforms reveals that continuous assessment, as opposed to one-off exams, offers a more comprehensive understanding of student capabilities.
  • By evaluating the E8’s plastic ban initiative, environmental rejuvenation and improved public health metrics affirm the necessity of eliminating single-use plastics.
  • Exploring the F9’s universal healthcare model, there’s a robust argument that public health services lead to more equitable societies and better health outcomes.
  • The success of the G10’s work-life balance policies underscores that a shorter workweek can lead to heightened productivity and enhanced employee satisfaction.

Case Study Thesis Statement Example for Research Paper

Case Study for  research paper thesis statement serves as a central hypothesis or primary insight derived from the chosen case. It succinctly captures the essence of the research findings and the implications they might hold, offering a foundation upon which the paper’s arguments and conclusions are built.

  • An extensive analysis of the H11 city’s water conservation techniques presents innovative methodologies that have achieved a 30% reduction in urban water consumption.
  • Investigating the I12’s coral reef restoration projects, recent advancements in marine biology have been instrumental in rejuvenating dying reef ecosystems.
  • The in-depth research on J13’s forest management strategies reveals the successful intersection of indigenous knowledge and modern conservation techniques.
  • A comprehensive study on the K14’s biodynamic farming practices demonstrates their impact on soil health and crop yield enhancement.
  • Researching L15’s approach to mental health, community-based interventions, and localized therapy models have shown significant efficacy.
  • By delving into M16’s urban waste management, innovative recycling technologies are revolutionizing urban sustainability and waste reduction.
  • The examination of N17’s digital literacy programs for seniors demonstrates adaptive pedagogies tailored for older learners, resulting in improved tech proficiency.
  • In-depth research on O18’s tidal energy projects presents groundbreaking advancements in harnessing marine energy for sustainable power generation.
  • A study of P19’s green building materials showcases the potential for sustainable construction without compromising on durability or aesthetics.
  • Extensive research on Q20’s citizen science initiatives has shed light on the profound impact of public engagement in scientific discoveries.

Case Study Essay Thesis Statement Example for Essay Writing

In essay writing, the case study thesis statement offers a central idea or perspective about the case at hand. It provides a roadmap for readers, indicating the essay’s direction and focus, and typically draws on the unique aspects of the case study to make broader observations or arguments.

  • The revitalization of the R21 town square serves as a testament to the profound impact of urban design on community engagement and cultural preservation.
  • Exploring the journey of S22’s artisanal chocolate brand offers insights into the nuances of combining traditional recipes with modern marketing.
  • The success story of the T23’s community library initiative illustrates the timeless importance of books and shared spaces in fostering community spirit.
  • Through a narrative on U24’s eco-tourism model, the delicate balance between conservation, commerce, and community involvement comes to the fore.
  • V25’s transformation from a tech-averse community to a digital hub showcases the ripple effects of targeted tech education and infrastructure investment.
  • The tale of W26’s fight against deforestation illuminates the intertwining of grassroots activism, governmental policy, and global collaboration.
  • X27’s journey in preserving endangered languages paints a vivid picture of the role of technology in safeguarding cultural heritage.
  • Diving into Y28’s transition from coal to solar energy portrays the challenges, victories, and transformative power of collective will.
  • The story of Z29’s grassroots sports academy gives a glimpse into the potential of talent nurtured through community support and dedication.
  • A narrative on A30’s urban art movement elucidates the transformative power of public art in redefining cityscapes and fostering local talent.

Does a case study have a thesis statement?

Yes, a case study often has a thesis statement, especially if it is intended for academic or formal publication. While the nature of case studies is to explore, analyze, and present specific situations or phenomena in detail, a thesis statement helps provide direction, focus, and clarity to the study. It serves as a clear indication of the main point or argument the author wishes to make, derived from their analysis of the case.

What is a thesis statement for a case study analysis?

A thesis statement for a case study analysis is a concise summary of the main insight or argument derived from reviewing and analyzing a particular case. It should be specific and based on the evidence found within the study, aiming to encapsulate the core findings or implications. This statement will guide the reader’s understanding of what the case study is ultimately trying to convey or the conclusions the author has drawn from their analysis.

How do you write a thesis statement for a case study? – Step by Step Guide

  • Select Your Case: Before you can write a thesis statement, you need to choose a case that offers enough substance and relevance. Your case should be representative or unique enough to provide meaningful insights.
  • Conduct Thorough Research: Dive deep into the details of your case. Understand its history, the key players involved, its significance, and its outcomes.
  • Identify Key Themes or Patterns: As you research, note down recurring themes or patterns that emerge. These will often hint at the broader implications of the case.
  • Formulate Your Argument: Based on your observations, craft an argument or insight about the case. Ask yourself what the case reveals about a broader phenomenon or what makes this case particularly significant.
  • Be Specific: Your thesis statement should be precise. Avoid vague or overly broad statements. Instead, focus on the specific insights or conclusions you’ve drawn from the case.
  • Write and Refine: Draft your thesis statement. It should be one or two sentences long, capturing the essence of your argument. Revisit and refine it to ensure clarity and conciseness.

Tips for Writing a Case Study Thesis Statement

  • Keep it Focused: Your thesis statement should be concise and directly related to the case in question. Avoid generalities or unrelated observations.
  • Be Evidence-Based: Ensure that your thesis statement can be backed up with evidence from the case study. It should be a result of your analysis, not a preconceived notion.
  • Avoid Jargon: Keep your thesis statement accessible. It should be understandable even to those unfamiliar with the specifics of the case.
  • Stay Objective: While your thesis statement will represent your analysis and perspective, it’s crucial to base it on facts and avoid unnecessary biases.
  • Seek Feedback: Once you’ve crafted your thesis statement, share it with peers or mentors. Their feedback can help refine your thesis and ensure it captures the essence of your case study effectively.

In conclusion, while a case study delves deep into specific instances, having a clear thesis statement is crucial to give direction to your study and offer readers a concise understanding of the case’s significance and your analysis.

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February 2024 Newsletter

2022 Three Minute Thesis (3MT) competition in Tink Ballroom

Three Minute Thesis (3MT)

Join us for the third annual  Three Minute Thesis (3MT™) competition  at Case Western Reserve University on Friday, February 16, from 12:40 to 3:15pm EST in the Tinkham Veale University Center Ballroom!

Developed by the University of Queensland and now held at over 900 institutions across more than 80 countries, 3MT celebrates the exciting research conducted by graduate students around the world. 3MT challenges students to explain their research and its importance in a way a general audience would understand in just three minutes with the aid of one single slide. The top-rated presenters will receive prizes and be celebrated at the 2023 Graduate Awards Ceremony in May. The first place winner will go on to represent CWRU and compete at the Midwest Association of Graduate Schools Regional Competition in March.

This year's keynote speaker for the 3MT competition will be John Gonzalez, the ever engaging Communications and Social Media Manager at Northeast Ohio Regional Sewer District. Attendees will receive a boxed lunch. Snacks and drinks will be available later in the afternoon. We ask that no eating take place during the competition presentations.

Learn more about  3MT at CWRU . Register on CampusGroups to  attend in-person  or  watch the livestream  from anywhere in the world.

PhD Graduates lined up on Main Quad before Commencement Convocation 2017

Commencement - May 17, 2024

The School of Graduate Studies Diploma Ceremony will be on Friday, May 17 at 2:00pm EDT. All graduating students are also invited to a University-wide Convocation on Wednesday, May 15. More details on Commencement 2024 will be posted in the coming weeks but you can review  additional information here .

Don't forget to register to attend the Commencement ceremonies! Registration will begin Friday, March 1 and end on Sunday, March 31. Even if you have already applied for graduation in SIS but you  must also  register to participate in Commencement; applying to graduate and registering for Commencement are  two entirely separate processes . When you register, you will be able to enter a preferred name and phonetic spelling and record your pronunciation.

Also, you can get  assistance ordering regalia  at doctoral fittings (March 5 and 15) or the Grad Fair (March 28-29).

Final Oral Defense

Doctoral candidates must submit the  Notification for Scheduling the Final Oral Exam  to Graduate Studies  at least three weeks prior  to the scheduled defense date. If you intend to graduate in May, you should pay careful attention to  submission deadlines  and plan accordingly. Dissertation defenses are to be held in-person. If special circumstances exist, students can petition Grad Studies for exceptions. See our  Graduation page  for more details.

Spring Break March 11-15

Students in the School of Graduate Studies receive a five-day break from classes and class activities corresponding to Spring Break in the undergraduate calendar, March 11 to 15. Please note that this exemption applies only to classes and class activities; faculty may still require students to perform research activities during these breaks.

As a reminder if you do stay on campus over the break, please confirm access availability as some buildings and services (KSL, gyms, shuttles, dining, etc) may have altered hours.

Clocktower at Biomedical Research Building (BRB)

Daylight Saving Time Begins in March

Daylight Saving Time (DST) for the United States will begin overnight Sunday, March 10. Before going to bed that Saturday night, make sure move forward one hour any clocks that do not automatically update so you're on time for any appointments the following week!

Incomplete (I) Grades from Fall 2023?

If you received an Incomplete ( I ) grade in the fall semester, you have until the date specified by your instructor -  but no later than the 11th week of class (Friday, March 29)  - to submit all outstanding work in order to have a final grade posted. If the Incomplete is not resolved by this date, the I grade will be converted to an F.  See our Incomplete Policy in the Bulletin  for more details.

Anti-Plagiarism Tools

Graduate students, postdoctoral scholars, and faculty should use  iThenticate  plagiarism detection software to ensure work is properly cited when writing theses and dissertations, preparing manuscripts for publication, and submitting proposals for research funding. iThenticate is freely available to the CWRU community at the University's Software Center. See here for  more information and how to download iThenticate .The University has also integrated  Turnitin , a digital plagiarism detection tool, into Canvas to help ensure student academic writing submissions are free of unintentional or intentional plagiarism. See here for  more information on Turnitin .

Verify Your Final Exams

Mark your calendars for final exams! Take a moment to verify your final exam dates and times with your syllabi and your professors. Make sure all of your travel plans for summer are  after  your final exams. Exams will not be rescheduled due to travel conflicts.

Resources & Opportunities

Selection of student winners of 2018 Graduate Awards

Nominate Students for Grad Studies Awards!

Nominations are now open for the 2024 Graduate Student Awards!

Faculty and academic departments with programs in the School of Graduate Studies are encouraged to nominate outstanding students for several prestigious awards to be honored at our ceremony on Wednesday, May 1. Some nominations can be submitted by students and community members. See  our submission page  for more details on each award including student eligibility, who is permitted to nominate, and what documentation is needed.

Send questions to  [email protected] . The deadline to submit nominations is Wednesday, March 20.

Submit Notification of Department Awards

Departments that sponsor awards for their students are encouraged to  submit notifications  to Grad Studies so we may include these winners in our ceremony on Wednesday, May 1. Any student in a program managed by the School of Graduate Studies who has received an award in the 2023-2024 academic year should be included so please send your notifications!

Send questions to  [email protected] . The deadline to submit notification of department awards is Wednesday, March 20.

Students Outside on Campus

Spoken English Sessions

  • Culture and Communication: February 16, 23, March 1, 4:25-5:15pm
  • Idioms and Expressions: March 29, April 5, 12, and 19, 4:25-5:15pm
  • SELP Workshops : Most Fridays 3:20-4:10pm
  • SELP English Conversation Hours Practice : Fridays 2:15-3:05pm
  • SELP Tutoring Program : one-on-one tutoring for grad students and postdocs

Register for the seminars and workshops on CampusGroups ; no registration needed for conversation hours. Most sessions are in Tomlinson 239. Graduate students can book tutoring sessions through Tutortrac . Postdocs can contact Eric Moore , the Director of Spoken English Language Programs (SELP).

CWRU Biophysics Day

In celebration of Biophysics Week (March 18-22), our Office of Postdoctoral Affairs invites the campus to Biophysics Day on Wednesday, March 20 at the Wolstein Research Building. See more and register on CampusGroups . Want to sign up to give a Flash Talk' Register by Sunday, March 3 and indicate your interest.

Additional Awards

  • Diversity Achievement Awards : February 16
  • Daniel Lewis Ravin, MD Award : March 7
  • Dr. Dorothy Pijan Student Leadership Awards : March 1
  • Timothy Calhoun Memorial Prize for Poetry : March 15
  • Eva L. Pancoast Memorial Fellowship : March 22

For new content almost ever day of interest to grad students - including other news on campus, important resources, upcoming events, and random fun stuff - please follow us on our social media platforms. Search for  @cwrusgs  on both  Facebook  and  Twitter  or click these links!

Snow covering the Arts Shield outside Yost Hall

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COMMENTS

  1. What Is a Case Study?

    Case studies are often a good choice in a thesis or dissertation. They keep your project focused and manageable when you don't have the time or resources to do large-scale research.

  2. Case Study vs. Research

    Introduction When it comes to conducting studies and gathering information, researchers have various methods at their disposal. Two commonly used approaches are case study and research. While both methods aim to explore and understand a particular subject, they differ in their approach, scope, and the type of data they collect.

  3. Case Study Methodology of Qualitative Research: Key Attributes and

    1. Case study is a research strategy, and not just a method/technique/process of data collection. 2. A case study involves a detailed study of the concerned unit of analysis within its natural setting.

  4. Case Study

    Case studies are often a good choice in a thesis or dissertation. They keep your project focused and manageable when you don't have the time or resources to do large-scale research.

  5. How to Write a Case Study: from Outline to Examples

    Explain what you will examine in the case study. Write an overview of the field you're researching. Make a thesis statement and sum up the results of your observation in a maximum of 2 sentences. Background. Provide background information and the most relevant facts. Isolate the issues.

  6. Writing a Case Study

    The purpose of a paper in the social sciences designed around a case study is to thoroughly investigate a subject of analysis in order to reveal a new understanding about the research problem and, in so doing, contributing new knowledge to what is already known from previous studies. In applied social sciences disciplines [e.g., education, social work, public administration, etc.], case ...

  7. Understanding the Different Types of Case Studies

    Basically put, an explanatory case study is 1 + 1 = 2. The results are not up for interpretation. A case study with a person or group would not be explanatory, as with humans, there will always be variables. There are always small variances that cannot be explained. However, event case studies can be explanatory.

  8. (PDF) The case study as a type of qualitative research

    In comparison to other types of qualitative research, case studies have been little understood both from a methodological point of view, where disagreements exist about whether case studies...

  9. Case Study Method: A Step-by-Step Guide for Business Researchers

    Yin (1994) defines case study as an empirical research activity that, by using versatile empirical material gathered in several different ways, examines a specific present-day event or action in a bounded environment. Case study objective is to do intensive research on a specific case, such as individual, group, institute, or community.

  10. Writing a Case Study Analysis

    Introduction Identify the key problems and issues in the case study. Formulate and include a thesis statement, summarizing the outcome of your analysis in 1-2 sentences. Background Set the scene: background information, relevant facts, and the most important issues. Demonstrate that you have researched the problems in this case study.

  11. Case study

    The case can refer to a real-life or hypothetical event, organisation, individual or group of people and/or issue. Depending upon your assignment, you will be asked to develop solutions to problems or recommendations for future action. Generally, a case study is either formatted as an essay or a report. If it is the latter, your assignment is ...

  12. (PDF) Case Study Research

    This study employed a qualitative case study methodology. The case study method is a research strategy that aims to gain an in-depth understanding of a specific phenomenon by collecting and ...

  13. Case Study ~ Guide with Definition, Types & Examples

    Case studies are used in different types of research for describing, evaluating and comparing different variables in a research problem. ... It gives researchers a method of studying the main characteristics, definitions and inferences about a case. They are appropriate for thesis and dissertations as they narrow the focus of a project. This ...

  14. How to Use Case Studies in Research: Guide and Examples

    1. Select a case. Once you identify the problem at hand and come up with questions, identify the case you will focus on. The study can provide insights into the subject at hand, challenge existing assumptions, propose a course of action, and/or open up new areas for further research. 2.

  15. Case study dissertation

    First, a case study provides a platform that allows you to study a situation in depth and produce the level of academic inquiry that is expected in a master's degree. In the context of any master's programme the dissertation operates as something of a showcase for a student's abilities.

  16. Distinguishing case study as a research method from case reports as a

    VARIATIONS ON CASE STUDY METHODOLOGY. Case study methodology is evolving and regularly reinterpreted. Comparative or multiple case studies are used as a tool for synthesizing information across time and space to research the impact of policy and practice in various fields of social research [].Because case study research is in-depth and intensive, there have been efforts to simplify the method ...

  17. How to use a case study in your masters dissertation

    First, a case study provides a platform that allows you to study a situation in depth and produce the level of academic inquiry that is expected in a master's degree. In the context of any master's programme the dissertation operates as something of a showcase for a student's abilities. It can easily make the difference between getting a ...

  18. The case study approach

    A case study is a research approach that is used to generate an in-depth, multi-faceted understanding of a complex issue in its real-life context. It is an established research design that is used extensively in a wide variety of disciplines, particularly in the social sciences. A case study can be defined in a variety of ways (Table 5 ), the ...

  19. Multiple Case Studies

    The difference between the single- and multiple-case study is the research design; however, they are within the same methodological framework (Yin, 2017). Multiple cases are selected so that "individual case studies either (a) predict similar results (a literal replication) or (b) predict contrasting results but for anticipatable reasons (a ...

  20. 7 Types of Case Study Methods

    1. Understanding Case Studies 2. What are the Types of Case Study? 3. Types of Subjects of Case Study 4. Benefits of Case Study for Students Understanding Case Studies Case studies are a type of research methodology. Case study research designs examine subjects, projects, or organizations to provide an analysis based on the evidence.

  21. What's the difference between action research and a case study?

    Action research is conducted in order to solve a particular issue immediately, while case studies are often conducted over a longer period of time and focus more on observing and analyzing a particular ongoing phenomenon. Frequently asked questions: Methodology What is differential attrition? What is the main purpose of action research?

  22. Case Study Thesis Statement Examples, How to Write, Tips

    100 Case Study Thesis Statement Examples. Case study thesis statements provide a concise encapsulation of the primary conclusions or insights gleaned from an in-depth analysis of a subject. They serve as a roadmap for readers, informing them of the study's focal points and key findings. To craft an effective case study thesis, it's ...

  23. Single case studies vs. multiple case studies: A comparative study

    This study attempts to answer when to write a single case study and when to write a multiple case study. It will further answer the benefits and disadvantages with the different types. The literature review, which is based on secondary sources, is about case studies. Then the literature review is discussed and analysed to reach a conclusion ...

  24. The Power of Preaching and Deliberative Dialogue to Catalyze ...

    This article explores different ways that preachers and congregations have used the sermon-dialogue-sermon process to address social issues in their churches and engage their local community. I begin with a brief review of the homiletic theory behind the emergence of dialogical preaching, including the ways I have integrated this theory into my own method of the sermon-dialogue-sermon (SDS ...

  25. School of Graduate Studies

    Three Minute Thesis (3MT) Join us for the third annual Three Minute Thesis (3MT™) competition at Case Western Reserve University on Friday, February 16, from 12:40 to 3:15pm EST in the Tinkham Veale University Center Ballroom! Developed by the University of Queensland and now held at over 900 institutions across more than 80 countries, 3MT celebrates the exciting research conducted by ...