difference between a case study and experiments

Case Study vs. Experiment: What's the Difference?

Key Differences

Comparison chart, generalization, preferred fields, case study and experiment definitions, when is a case study used, what is an experiment, how do case studies gather data, can case studies be generalized, what fields commonly use case studies, what type of data do experiments produce, can a case study include quantitative data, what is a case study, what is the main purpose of an experiment, is bias a concern in case studies, are experiments replicable, in which fields are experiments predominant, how do experiments impact scientific knowledge, what is a longitudinal case study, can experiments be conducted in natural settings, what is the role of control in experiments, how long can a case study last, what ethical considerations are involved in experiments, can case studies be used to test hypotheses, how is replicability ensured in experiments.

Trending Comparisons

Popular Comparisons

New Comparisons

Distinguishing Between Case Studies & Experiments

Case Study vs Experiment

Case studies and experiments are two distinct research methods used across various disciplines, providing researchers with the ability to study and analyze a subject through different approaches. This variety in research methods allows the researcher to gather both qualitative and quantitative data, cross-check the data, and assign greater validity to the conclusions and overall findings of the research. A case study is a research method in which the researcher explores the subject in depth, while an experiment is a research method where two specific groups or variables are used to test a hypothesis. This article will examine the differences between case study and experiment further.

What is a Case Study?

A case study is a research method where an individual, event, or significant place is studied in depth. In the case of an individual, the researcher studies the person’s life history, which can include important days or special experiences. The case study method is used in various social sciences such as sociology, anthropology, and psychology. Through a case study, the researcher can identify and understand the subjective experiences of an individual regarding a specific topic. For example, a researcher studying the impact of second rape on the lives of rape victims can conduct several case studies to understand the subjective experiences of individuals and social mechanisms that contribute to this phenomenon. The case study is a qualitative research method that can be subjective.

What is an Experiment?

An experiment, unlike a case study, can be classified as a quantitative research method, as it provides statistically significant data and an objective, empirical approach. Experiments are primarily used in natural sciences, as they allow the scientist to control variables. In social sciences, controlling variables can be challenging and may lead to faulty conclusions. In an experiment, there are mainly two variables: the independent variable and the dependent variable. The researcher tries to test their hypothesis by manipulating these variables. There are different types of experiments, such as laboratory experiments (conducted in laboratories where conditions can be strictly controlled) and natural experiments (which take place in real-life settings). As seen, case study methods and experiments are very different from one another. However, most researchers prefer to use triangulation when conducting research to minimize biases.

Key Takeaways

• Case studies are in-depth explorations of a subject, providing qualitative data, while experiments test hypotheses by manipulating variables, providing quantitative data.
• Experiments are primarily used in natural sciences, whereas case studies are primarily used in social sciences.
• Experiments involve testing the correlation between two variables (independent and dependent), while case studies focus on exploring a subject in depth without testing correlations between variables.

LEAVE A REPLY Cancel reply

Save my name, email, and website in this browser for the next time I comment.

Related Articles

Difference between power & authority, distinguishing could of & could have, distinguishing pixie & bob haircuts, distinguishing between debate & discussion, distinguishing between dialogue & conversation, distinguishing between a present & a gift, distinguishing between will & can, distinguishing between up & upon.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, generate accurate citations for free.

• Knowledge Base

Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, 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 analyze the case, other interesting articles.

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.

Here's why students love Scribbr's proofreading services

Discover proofreading & editing

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

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

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.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

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

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

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.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

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 analyze 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.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.

McCombes, S. (2023, November 20). What Is a Case Study? | Definition, Examples & Methods. Scribbr. Retrieved June 24, 2024, from https://www.scribbr.com/methodology/case-study/

Is this article helpful?

Shona McCombes

Other students also liked, primary vs. secondary sources | difference & examples, what is a theoretical framework | guide to organizing, what is action research | definition & examples, get unlimited documents corrected.

✔ Free APA citation check included ✔ Unlimited document corrections ✔ Specialized in correcting academic texts

Case Study vs Experiment: Know the Difference

A case study and experiment are the two prominent approaches often used at the forefront of scholarly inquiry. While case studies study the complexities of real-life situations, aiming for depth and contextual understanding, experiments seek to uncover causal relationships through controlled manipulation and observation. Both these research methods are indispensable tools in understanding phenomena, yet they diverge significantly in their approaches, aims, and applications.

In this article, we’ll unpack the key differences between case studies and experiments, exploring their strengths, limitations, and the unique insights they offer when working with quantitative data. In the meantime, feel free to use our specialized case study writing service if you seek to streamline your efforts when handling this academic task.

What Is a Case Study?

A case study is a research method that involves an in-depth examination of a particular individual, group, event, or phenomenon within its real-life context. It aims to provide a detailed and comprehensive analysis of the subject under investigation, often using multiple data sources such as interviews, observations, documents, and archival records.

The case study method is used in psychology, sociology, anthropology, education, and business to explore complex issues, understand unique situations, and generate rich, contextualized insights. They allow scholars to explore the intricacies of real-world phenomena, uncovering patterns, relationships, and underlying factors in social sciences that may not be readily apparent through other research methods.

Overall, case studies offer a holistic and nuanced understanding of the subject of interest, facilitating deeper exploration and interpretation of complex social and human phenomena. If you’re struggling with this assignment, simply say, ‘ write my case study for me ,’ and our experts will help you promptly.

What Is an Experiment?

Compared to the case study method, an experiment investigates cause-and-effect relationships by systematically manipulating one or more variables and observing the effects on other variables. In an experiment, students aim to establish causal relationships between an independent variable (the factors being manipulated) and a dependent variable (the outcomes being measured).

Experiments are characterized by their controlled and systematic approach, often involving the random assignment of participants to different experimental conditions to minimize bias and ensure the validity of the findings. They are commonly used in such fields of social sciences as psychology, biology, physics, and medicine to test hypotheses, identify causal mechanisms, and provide empirical evidence for theories.

An experiment method allows scholars to establish causal relationships with high confidence, providing valuable insights into the underlying mechanisms of behavior, natural phenomena, and social processes. Other research methods include:

• Survey method: Collects research data from individuals through questionnaires or interviews to gather information about attitudes, opinions, behaviors, and characteristics of a population.
• Observation method: Systematically observes and records behavior, events, or phenomena as they naturally occur in real-life settings to study social interactions, environmental factors, or naturalistic behavior.
• Qualitative and quantitative research method: Qualitative research explores meanings, perceptions, and experiences using interviews or content analysis, while quantitative research analyzes numerical data to test hypotheses or identify patterns and relationships.
• Archival research method: Analyzes existing documents, records, or data sources such as historical documents or organizational archives to investigate trends, patterns, or historical events.
• Action research method: Involves collaboration between scholars and practitioners to identify and address practical problems or challenges within specific organizational or community contexts, aiming to generate actionable knowledge and facilitate positive change.

Difference Between Case Study and Experiment

Case study and experiment definitions.

A case study method involves a deep investigation into a specific individual, group, event, or phenomenon within its real-life context, aiming to provide rich and detailed insights into complex issues. Learners gather research data from multiple sources, such as interviews, observations, documents, and archival records, to comprehensively understand the subject under study.

Case studies are particularly useful for exploring unique or rare phenomena, offering a holistic view that captures the intricacies and nuances of the situation. However, findings from case studies may be challenging to generalize to broader populations due to the specificity of the case and the lack of experimental control. To learn more about how to write a case study , please refer to our guide.

An experiment is a research method that systematically manipulates one or more variables to observe their effects on other variables, aiming to establish cause-and-effect relationships under controlled conditions. Researchers design experiments with high control over variables, often using standardized procedures and quantitative measures for research data collection.

Experiments are well-suited for testing hypotheses and identifying causal relationships in controlled environments, allowing educatees to conclude the effects of specific interventions or manipulations. However, experiments may lack the depth and contextual richness of case studies, and findings are typically limited to the specific conditions of the experiment.

Case Study and Experiment Characteristic Features

• In case studies , variables are observed rather than manipulated. Researchers do not typically control variables; instead, they examine how naturally occurring variables interact within the case context.
• Experiments involve manipulating one or more variables to observe their effects on other variables. Students actively control and manipulate variables to test hypotheses and establish cause-and-effect relationships.
• Case studies may not always begin with a specific hypothesis. Instead, researchers often seek to generate hypotheses based on the data collected during the study.
• Experiments are typically conducted to test specific hypotheses. Researchers formulate a hypothesis based on existing theory or observations, and the experiment is designed to confirm or refute this hypothesis.

Manipulating Variables

• Variables are not manipulated in case studies . Instead, researchers observe and analyze how naturally occurring variables influence the phenomenon of interest.
• In experiments , researchers actively manipulate one independent or dependent variable or more to observe their effects on other variables. This manipulation allows researchers to establish causal relationships between variables.
• Case studies often involve collecting qualitative data from multiple sources, such as interviews, observations, documents, and archival records. Researchers analyze this research data to provide a detailed and contextualized understanding of the case.
• Experiments typically involve the collection of quantitative data using standardized procedures and measures. Researchers use statistical analysis to interpret the research data and draw conclusions about the effects of the manipulated variables.

Areas of Implementation

• Case studies are widely used in social sciences, such as psychology, sociology, anthropology, education, and business, to explore complex issues, understand unique situations, and generate rich, contextualized insights.
• Experiments are common in fields such as psychology, biology, physics, and medicine, where researchers seek to test hypotheses, identify causal mechanisms, and provide empirical evidence for theories through controlled manipulation and observation.

Frequently asked questions

She was flawless! first time using a website like this, I've ordered article review and i totally adored it! grammar punctuation, content - everything was on point

This writer is my go to, because whenever I need someone who I can trust my task to - I hire Joy. She wrote almost every paper for me for the last 2 years

Term paper done up to a highest standard, no revisions, perfect communication. 10s across the board!!!!!!!

I send him instructions and that's it. my paper was done 10 hours later, no stupid questions, he nailed it.

Sometimes I wonder if Michael is secretly a professor because he literally knows everything. HE DID SO WELL THAT MY PROF SHOWED MY PAPER AS AN EXAMPLE. unbelievable, many thanks

New Posts to Your Inbox!

Stay in touch

Case Study vs. Single-Case Experimental Designs

What's the difference.

Case study and single-case experimental designs are both research methods used in psychology and other social sciences to investigate individual cases or subjects. However, they differ in their approach and purpose. Case studies involve in-depth examination of a single case, such as an individual, group, or organization, to gain a comprehensive understanding of the phenomenon being studied. On the other hand, single-case experimental designs focus on studying the effects of an intervention or treatment on a single subject over time. These designs use repeated measures and control conditions to establish cause-and-effect relationships. While case studies provide rich qualitative data, single-case experimental designs offer more rigorous experimental control and allow for the evaluation of treatment effectiveness.

Further Detail

Introduction.

When conducting research in various fields, it is essential to choose the appropriate study design to answer research questions effectively. Two commonly used designs are case study and single-case experimental designs. While both approaches aim to provide valuable insights into specific phenomena, they differ in several key attributes. This article will compare and contrast the attributes of case study and single-case experimental designs, highlighting their strengths and limitations.

Definition and Purpose

A case study is an in-depth investigation of a particular individual, group, or event. It involves collecting and analyzing qualitative or quantitative data to gain a comprehensive understanding of the subject under study. Case studies are often used to explore complex phenomena, generate hypotheses, or provide detailed descriptions of unique cases.

On the other hand, single-case experimental designs are a type of research design that focuses on studying a single individual or a small group over time. These designs involve manipulating an independent variable and measuring its effects on a dependent variable. Single-case experimental designs are particularly useful for examining cause-and-effect relationships and evaluating the effectiveness of interventions or treatments.

Data Collection and Analysis

In terms of data collection, case studies rely on various sources such as interviews, observations, documents, and artifacts. Researchers often employ multiple methods to gather rich and diverse data, allowing for a comprehensive analysis of the case. The data collected in case studies are typically qualitative in nature, although quantitative data may also be included.

In contrast, single-case experimental designs primarily rely on quantitative data collection methods. Researchers use standardized measures and instruments to collect data on the dependent variable before, during, and after the manipulation of the independent variable. This allows for a systematic analysis of the effects of the intervention or treatment on the individual or group being studied.

Generalizability

One of the key differences between case studies and single-case experimental designs is their generalizability. Case studies are often conducted on unique or rare cases, making it challenging to generalize the findings to a larger population. The focus of case studies is on providing detailed insights into specific cases rather than making broad generalizations.

On the other hand, single-case experimental designs aim to establish causal relationships and can provide evidence for generalizability. By systematically manipulating the independent variable and measuring its effects on the dependent variable, researchers can draw conclusions about the effectiveness of interventions or treatments that may be applicable to similar cases or populations.

Internal Validity

Internal validity refers to the extent to which a study accurately measures the cause-and-effect relationship between variables. In case studies, establishing internal validity can be challenging due to the lack of control over extraneous variables. The presence of multiple data sources and the potential for subjective interpretation may also introduce bias.

In contrast, single-case experimental designs prioritize internal validity by employing rigorous control over extraneous variables. Researchers carefully design the intervention or treatment, implement it consistently, and measure the dependent variable under controlled conditions. This allows for a more confident determination of the causal relationship between the independent and dependent variables.

Time and Resources

Case studies often require significant time and resources due to their in-depth nature. Researchers need to spend considerable time collecting and analyzing data from various sources, conducting interviews, and immersing themselves in the case. Additionally, case studies may involve multiple researchers or a research team, further increasing the required resources.

On the other hand, single-case experimental designs can be more time and resource-efficient. Since they focus on a single individual or a small group, data collection and analysis can be more streamlined. Researchers can also implement interventions or treatments in a controlled manner, reducing the time and resources needed for data collection.

Ethical Considerations

Both case studies and single-case experimental designs require researchers to consider ethical implications. In case studies, researchers must ensure the privacy and confidentiality of the individuals or groups being studied. Informed consent and ethical guidelines for data collection and analysis should be followed to protect the rights and well-being of the participants.

Similarly, in single-case experimental designs, researchers must consider ethical considerations when implementing interventions or treatments. The well-being and safety of the individual or group being studied should be prioritized, and informed consent should be obtained. Additionally, researchers should carefully monitor and evaluate the potential risks and benefits associated with the intervention or treatment.

Case studies and single-case experimental designs are valuable research approaches that offer unique insights into specific phenomena. While case studies provide in-depth descriptions and exploratory analyses of individual cases, single-case experimental designs focus on establishing causal relationships and evaluating interventions or treatments. Researchers should carefully consider the attributes and goals of their study when choosing between these two designs, ensuring that the selected approach aligns with their research questions and objectives.

Comparisons may contain inaccurate information about people, places, or facts. Please report any issues.

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Methodology
• Case Study | Definition, Examples & Methods

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.

Prevent plagiarism, run a free check.

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.

Cite this Scribbr article

If you want to cite this source, you can copy and paste the citation or click the ‘Cite this Scribbr article’ button to automatically add the citation to our free Reference Generator.

McCombes, S. (2023, January 30). Case Study | Definition, Examples & Methods. Scribbr. Retrieved 24 June 2024, from https://www.scribbr.co.uk/research-methods/case-studies/

Is this article helpful?

Shona McCombes

Other students also liked, correlational research | guide, design & examples, a quick guide to experimental design | 5 steps & examples, descriptive research design | definition, methods & examples.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• J Med Libr Assoc
• v.107(1); 2019 Jan

Distinguishing case study as a research method from case reports as a publication type

The purpose of this editorial is to distinguish between case reports and case studies. In health, case reports are familiar ways of sharing events or efforts of intervening with single patients with previously unreported features. As a qualitative methodology, case study research encompasses a great deal more complexity than a typical case report and often incorporates multiple streams of data combined in creative ways. The depth and richness of case study description helps readers understand the case and whether findings might be applicable beyond that setting.

Single-institution descriptive reports of library activities are often labeled by their authors as “case studies.” By contrast, in health care, single patient retrospective descriptions are published as “case reports.” Both case reports and case studies are valuable to readers and provide a publication opportunity for authors. A previous editorial by Akers and Amos about improving case studies addresses issues that are more common to case reports; for example, not having a review of the literature or being anecdotal, not generalizable, and prone to various types of bias such as positive outcome bias [ 1 ]. However, case study research as a qualitative methodology is pursued for different purposes than generalizability. The authors’ purpose in this editorial is to clearly distinguish between case reports and case studies. We believe that this will assist authors in describing and designating the methodological approach of their publications and help readers appreciate the rigor of well-executed case study research.

Case reports often provide a first exploration of a phenomenon or an opportunity for a first publication by a trainee in the health professions. In health care, case reports are familiar ways of sharing events or efforts of intervening with single patients with previously unreported features. Another type of study categorized as a case report is an “N of 1” study or single-subject clinical trial, which considers an individual patient as the sole unit of observation in a study investigating the efficacy or side effect profiles of different interventions. Entire journals have evolved to publish case reports, which often rely on template structures with limited contextualization or discussion of previous cases. Examples that are indexed in MEDLINE include the American Journal of Case Reports , BMJ Case Reports, Journal of Medical Case Reports, and Journal of Radiology Case Reports . Similar publications appear in veterinary medicine and are indexed in CAB Abstracts, such as Case Reports in Veterinary Medicine and Veterinary Record Case Reports .

As a qualitative methodology, however, case study research encompasses a great deal more complexity than a typical case report and often incorporates multiple streams of data combined in creative ways. Distinctions include the investigator’s definitions and delimitations of the case being studied, the clarity of the role of the investigator, the rigor of gathering and combining evidence about the case, and the contextualization of the findings. Delimitation is a term from qualitative research about setting boundaries to scope the research in a useful way rather than describing the narrow scope as a limitation, as often appears in a discussion section. The depth and richness of description helps readers understand the situation and whether findings from the case are applicable to their settings.

CASE STUDY AS A RESEARCH METHODOLOGY

Case study as a qualitative methodology is an exploration of a time- and space-bound phenomenon. As qualitative research, case studies require much more from their authors who are acting as instruments within the inquiry process. In the case study methodology, a variety of methodological approaches may be employed to explain the complexity of the problem being studied [ 2 , 3 ].

Leading authors diverge in their definitions of case study, but a qualitative research text introduces case study as follows:

Case study research is defined as a qualitative approach in which the investigator explores a real-life, contemporary bounded system (a case) or multiple bound systems (cases) over time, through detailed, in-depth data collection involving multiple sources of information, and reports a case description and case themes. The unit of analysis in the case study might be multiple cases (a multisite study) or a single case (a within-site case study). [ 4 ]

Methodologists writing core texts on case study research include Yin [ 5 ], Stake [ 6 ], and Merriam [ 7 ]. The approaches of these three methodologists have been compared by Yazan, who focused on six areas of methodology: epistemology (beliefs about ways of knowing), definition of cases, design of case studies, and gathering, analysis, and validation of data [ 8 ]. For Yin, case study is a method of empirical inquiry appropriate to determining the “how and why” of phenomena and contributes to understanding phenomena in a holistic and real-life context [ 5 ]. Stake defines a case study as a “well-bounded, specific, complex, and functioning thing” [ 6 ], while Merriam views “the case as a thing, a single entity, a unit around which there are boundaries” [ 7 ].

Case studies are ways to explain, describe, or explore phenomena. Comments from a quantitative perspective about case studies lacking rigor and generalizability fail to consider the purpose of the case study and how what is learned from a case study is put into practice. Rigor in case studies comes from the research design and its components, which Yin outlines as (a) the study’s questions, (b) the study’s propositions, (c) the unit of analysis, (d) the logic linking the data to propositions, and (e) the criteria for interpreting the findings [ 5 ]. Case studies should also provide multiple sources of data, a case study database, and a clear chain of evidence among the questions asked, the data collected, and the conclusions drawn [ 5 ].

Sources of evidence for case studies include interviews, documentation, archival records, direct observations, participant-observation, and physical artifacts. One of the most important sources for data in qualitative case study research is the interview [ 2 , 3 ]. In addition to interviews, documents and archival records can be gathered to corroborate and enhance the findings of the study. To understand the phenomenon or the conditions that created it, direct observations can serve as another source of evidence and can be conducted throughout the study. These can include the use of formal and informal protocols as a participant inside the case or an external or passive observer outside of the case [ 5 ]. Lastly, physical artifacts can be observed and collected as a form of evidence. With these multiple potential sources of evidence, the study methodology includes gathering data, sense-making, and triangulating multiple streams of data. Figure 1 shows an example in which data used for the case started with a pilot study to provide additional context to guide more in-depth data collection and analysis with participants.

Key sources of data for a sample case study

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 [ 9 ]. Because case study research is in-depth and intensive, there have been efforts to simplify the method or select useful components of cases for focused analysis. Micro-case study is a term that is occasionally used to describe research on micro-level cases [ 10 ]. These are cases that occur in a brief time frame, occur in a confined setting, and are simple and straightforward in nature. A micro-level case describes a clear problem of interest. Reporting is very brief and about specific points. The lack of complexity in the case description makes obvious the “lesson” that is inherent in the case; although no definitive “solution” is necessarily forthcoming, making the case useful for discussion. A micro-case write-up can be distinguished from a case report by its focus on briefly reporting specific features of a case or cases to analyze or learn from those features.

DATABASE INDEXING OF CASE REPORTS AND CASE STUDIES

Disciplines such as education, psychology, sociology, political science, and social work regularly publish rich case studies that are relevant to particular areas of health librarianship. Case reports and case studies have been defined as publication types or subject terms by several databases that are relevant to librarian authors: MEDLINE, PsycINFO, CINAHL, and ERIC. Library, Information Science & Technology Abstracts (LISTA) does not have a subject term or publication type related to cases, despite many being included in the database. Whereas “Case Reports” are the main term used by MEDLINE’s Medical Subject Headings (MeSH) and PsycINFO’s thesaurus, CINAHL and ERIC use “Case Studies.”

Case reports in MEDLINE and PsycINFO focus on clinical case documentation. In MeSH, “Case Reports” as a publication type is specific to “clinical presentations that may be followed by evaluative studies that eventually lead to a diagnosis” [ 11 ]. “Case Histories,” “Case Studies,” and “Case Study” are all entry terms mapping to “Case Reports”; however, guidance to indexers suggests that “Case Reports” should not be applied to institutional case reports and refers to the heading “Organizational Case Studies,” which is defined as “descriptions and evaluations of specific health care organizations” [ 12 ].

PsycINFO’s subject term “Case Report” is “used in records discussing issues involved in the process of conducting exploratory studies of single or multiple clinical cases.” The Methodology index offers clinical and non-clinical entries. “Clinical Case Study” is defined as “case reports that include disorder, diagnosis, and clinical treatment for individuals with mental or medical illnesses,” whereas “Non-clinical Case Study” is a “document consisting of non-clinical or organizational case examples of the concepts being researched or studied. The setting is always non-clinical and does not include treatment-related environments” [ 13 ].

Both CINAHL and ERIC acknowledge the depth of analysis in case study methodology. The CINAHL scope note for the thesaurus term “Case Studies” distinguishes between the document and the methodology, though both use the same term: “a review of a particular condition, disease, or administrative problem. Also, a research method that involves an in-depth analysis of an individual, group, institution, or other social unit. For material that contains a case study, search for document type: case study.” The ERIC scope note for the thesaurus term “Case Studies” is simple: “detailed analyses, usually focusing on a particular problem of an individual, group, or organization” [ 14 ].

PUBLICATION OF CASE STUDY RESEARCH IN LIBRARIANSHIP

We call your attention to a few examples published as case studies in health sciences librarianship to consider how their characteristics fit with the preceding definitions of case reports or case study research. All present some characteristics of case study research, but their treatment of the research questions, richness of description, and analytic strategies vary in depth and, therefore, diverge at some level from the qualitative case study research approach. This divergence, particularly in richness of description and analysis, may have been constrained by the publication requirements.

As one example, a case study by Janke and Rush documented a time- and context-bound collaboration involving a librarian and a nursing faculty member [ 15 ]. Three objectives were stated: (1) describing their experience of working together on an interprofessional research team, (2) evaluating the value of the librarian role from librarian and faculty member perspectives, and (3) relating findings to existing literature. Elements that signal the qualitative nature of this case study are that the authors were the research participants and their use of the term “evaluation” is reflection on their experience. This reads like a case study that could have been enriched by including other types of data gathered from others engaging with this team to broaden the understanding of the collaboration.

As another example, the description of the academic context is one of the most salient components of the case study written by Clairoux et al., which had the objectives of (1) describing the library instruction offered and learning assessments used at a single health sciences library and (2) discussing the positive outcomes of instruction in that setting [ 16 ]. The authors focus on sharing what the institution has done more than explaining why this institution is an exemplar to explore a focused question or understand the phenomenon of library instruction. However, like a case study, the analysis brings together several streams of data including course attendance, online material page views, and some discussion of results from surveys. This paper reads somewhat in between an institutional case report and a case study.

The final example is a single author reporting on a personal experience of creating and executing the role of research informationist for a National Institutes of Health (NIH)–funded research team [ 17 ]. There is a thoughtful review of the informationist literature and detailed descriptions of the institutional context and the process of gaining access to and participating in the new role. However, the motivating question in the abstract does not seem to be fully addressed through analysis from either the reflective perspective of the author as the research participant or consideration of other streams of data from those involved in the informationist experience. The publication reads more like a case report about this informationist’s experience than a case study that explores the research informationist experience through the selection of this case.

All of these publications are well written and useful for their intended audiences, but in general, they are much shorter and much less rich in depth than case studies published in social sciences research. It may be that the authors have been constrained by word counts or page limits. For example, the submission category for Case Studies in the Journal of the Medical Library Association (JMLA) limited them to 3,000 words and defined them as “articles describing the process of developing, implementing, and evaluating a new service, program, or initiative, typically in a single institution or through a single collaborative effort” [ 18 ]. This definition’s focus on novelty and description sounds much more like the definition of case report than the in-depth, detailed investigation of a time- and space-bound problem that is often examined through case study research.

Problem-focused or question-driven case study research would benefit from the space provided for Original Investigations that employ any type of quantitative or qualitative method of analysis. One of the best examples in the JMLA of an in-depth multiple case study that was authored by a librarian who published the findings from her doctoral dissertation represented all the elements of a case study. In eight pages, she provided a theoretical basis for the research question, a pilot study, and a multiple case design, including integrated data from interviews and focus groups [ 19 ].

We have distinguished between case reports and case studies primarily to assist librarians who are new to research and critical appraisal of case study methodology to recognize the features that authors use to describe and designate the methodological approaches of their publications. For researchers who are new to case research methodology and are interested in learning more, Hancock and Algozzine provide a guide [ 20 ].

We hope that JMLA readers appreciate the rigor of well-executed case study research. We believe that distinguishing between descriptive case reports and analytic case studies in the journal’s submission categories will allow the depth of case study methodology to increase. We also hope that authors feel encouraged to pursue submitting relevant case studies or case reports for future publication.

Editor’s note: In response to this invited editorial, the Journal of the Medical Library Association will consider manuscripts employing rigorous qualitative case study methodology to be Original Investigations (fewer than 5,000 words), whereas manuscripts describing the process of developing, implementing, and assessing a new service, program, or initiative—typically in a single institution or through a single collaborative effort—will be considered to be Case Reports (formerly known as Case Studies; fewer than 3,000 words).

• En español – ExME
• Em português – EME

An introduction to different types of study design

Posted on 6th April 2021 by Hadi Abbas

Study designs are the set of methods and procedures used to collect and analyze data in a study.

Broadly speaking, there are 2 types of study designs: descriptive studies and analytical studies.

Descriptive studies

• Describes specific characteristics in a population of interest
• The most common forms are case reports and case series
• In a case report, we discuss our experience with the patient’s symptoms, signs, diagnosis, and treatment
• In a case series, several patients with similar experiences are grouped.

Analytical Studies

Analytical studies are of 2 types: observational and experimental.

Observational studies are studies that we conduct without any intervention or experiment. In those studies, we purely observe the outcomes.  On the other hand, in experimental studies, we conduct experiments and interventions.

Observational studies

Observational studies include many subtypes. Below, I will discuss the most common designs.

Cross-sectional study:

• This design is transverse where we take a specific sample at a specific time without any follow-up
• It allows us to calculate the frequency of disease ( p revalence ) or the frequency of a risk factor
• This design is easy to conduct
• For example – if we want to know the prevalence of migraine in a population, we can conduct a cross-sectional study whereby we take a sample from the population and calculate the number of patients with migraine headaches.

Cohort study:

• We conduct this study by comparing two samples from the population: one sample with a risk factor while the other lacks this risk factor
• It shows us the risk of developing the disease in individuals with the risk factor compared to those without the risk factor ( RR = relative risk )
• Prospective : we follow the individuals in the future to know who will develop the disease
• Retrospective : we look to the past to know who developed the disease (e.g. using medical records)
• This design is the strongest among the observational studies
• For example – to find out the relative risk of developing chronic obstructive pulmonary disease (COPD) among smokers, we take a sample including smokers and non-smokers. Then, we calculate the number of individuals with COPD among both.

Case-Control Study:

• We conduct this study by comparing 2 groups: one group with the disease (cases) and another group without the disease (controls)
• This design is always retrospective
•  We aim to find out the odds of having a risk factor or an exposure if an individual has a specific disease (Odds ratio)
•  Relatively easy to conduct
• For example – we want to study the odds of being a smoker among hypertensive patients compared to normotensive ones. To do so, we choose a group of patients diagnosed with hypertension and another group that serves as the control (normal blood pressure). Then we study their smoking history to find out if there is a correlation.

Experimental Studies

• Also known as interventional studies
• Can involve animals and humans
• Pre-clinical trials involve animals
• Clinical trials are experimental studies involving humans
• In clinical trials, we study the effect of an intervention compared to another intervention or placebo. As an example, I have listed the four phases of a drug trial:

I:  We aim to assess the safety of the drug ( is it safe ? )

II: We aim to assess the efficacy of the drug ( does it work ? )

III: We want to know if this drug is better than the old treatment ( is it better ? )

IV: We follow-up to detect long-term side effects ( can it stay in the market ? )

• In randomized controlled trials, one group of participants receives the control, while the other receives the tested drug/intervention. Those studies are the best way to evaluate the efficacy of a treatment.

Finally, the figure below will help you with your understanding of different types of study designs.

References (pdf)

You may also be interested in the following blogs for further reading:

An introduction to randomized controlled trials

Case-control and cohort studies: a brief overview

Cohort studies: prospective and retrospective designs

Prevalence vs Incidence: what is the difference?

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

No Comments on An introduction to different types of study design

you are amazing one!! if I get you I’m working with you! I’m student from Ethiopian higher education. health sciences student

Very informative and easy understandable

You are my kind of doctor. Do not lose sight of your objective.

Wow very erll explained and easy to understand

I’m Khamisu Habibu community health officer student from Abubakar Tafawa Balewa university teaching hospital Bauchi, Nigeria, I really appreciate your write up and you have make it clear for the learner. thank you

well understood,thank you so much

Well understood…thanks

Simply explained. Thank You.

Thanks a lot for this nice informative article which help me to understand different study designs that I felt difficult before

That’s lovely to hear, Mona, thank you for letting the author know how useful this was. If there are any other particular topics you think would be useful to you, and are not already on the website, please do let us know.

it is very informative and useful.

thank you statistician

Fabulous to hear, thank you John.

Thanks for this information

Thanks so much for this information….I have clearly known the types of study design Thanks

That’s so good to hear, Mirembe, thank you for letting the author know.

Very helpful article!! U have simplified everything for easy understanding

I’m a health science major currently taking statistics for health care workers…this is a challenging class…thanks for the simified feedback.

That’s good to hear this has helped you. Hopefully you will find some of the other blogs useful too. If you see any topics that are missing from the website, please do let us know!

Hello. I liked your presentation, the fact that you ranked them clearly is very helpful to understand for people like me who is a novelist researcher. However, I was expecting to read much more about the Experimental studies. So please direct me if you already have or will one day. Thank you

Dear Ay. My sincere apologies for not responding to your comment sooner. You may find it useful to filter the blogs by the topic of ‘Study design and research methods’ – here is a link to that filter: https://s4be.cochrane.org/blog/topic/study-design/ This will cover more detail about experimental studies. Or have a look on our library page for further resources there – you’ll find that on the ‘Resources’ drop down from the home page.

However, if there are specific things you feel you would like to learn about experimental studies, that are missing from the website, it would be great if you could let me know too. Thank you, and best of luck. Emma

Great job Mr Hadi. I advise you to prepare and study for the Australian Medical Board Exams as soon as you finish your undergrad study in Lebanon. Good luck and hope we can meet sometime in the future. Regards ;)

You have give a good explaination of what am looking for. However, references am not sure of where to get them from.

Subscribe to our newsletter

You will receive our monthly newsletter and free access to Trip Premium.

Related Articles

Cluster Randomized Trials: Concepts

This blog summarizes the concepts of cluster randomization, and the logistical and statistical considerations while designing a cluster randomized controlled trial.

Expertise-based Randomized Controlled Trials

This blog summarizes the concepts of Expertise-based randomized controlled trials with a focus on the advantages and challenges associated with this type of study.

A well-designed cohort study can provide powerful results. This blog introduces prospective and retrospective cohort studies, discussing the advantages, disadvantages and use of these type of study designs.

Quantitative study designs: Case Studies/ Case Report/ Case Series

Quantitative study designs.

• Introduction
• Cohort Studies
• Randomised Controlled Trial
• Case Control
• Cross-Sectional Studies
• Study Designs Home

Case Study / Case Report / Case Series

Some famous examples of case studies are John Martin Marlow’s case study on Phineas Gage (the man who had a railway spike through his head) and Sigmund Freud’s case studies, Little Hans and The Rat Man. Case studies are widely used in psychology to provide insight into unusual conditions.

A case study, also known as a case report, is an in depth or intensive study of a single individual or specific group, while a case series is a grouping of similar case studies / case reports together.

A case study / case report can be used in the following instances:

• where there is atypical or abnormal behaviour or development
• an unexplained outcome to treatment
• an emerging disease or condition

The stages of a Case Study / Case Report / Case Series

Which clinical questions does Case Study / Case Report / Case Series best answer?

Emerging conditions, adverse reactions to treatments, atypical / abnormal behaviour, new programs or methods of treatment – all of these can be answered with case studies /case reports / case series. They are generally descriptive studies based on qualitative data e.g. observations, interviews, questionnaires, diaries, personal notes or clinical notes.

What are the advantages and disadvantages to consider when using Case Studies/ Case Reports and Case Series ?

What are the pitfalls to look for?

One pitfall that has occurred in some case studies is where two common conditions/treatments have been linked together with no comprehensive data backing up the conclusion. A hypothetical example could be where high rates of the common cold were associated with suicide when the cohort also suffered from depression.

Critical appraisal tools 

To assist with critically appraising Case studies / Case reports / Case series there are some tools / checklists you can use.

JBI Critical Appraisal Checklist for Case Series

JBI Critical Appraisal Checklist for Case Reports

Real World Examples

Some Psychology case study / case report / case series examples

Capp, G. (2015). Our community, our schools : A case study of program design for school-based mental health services. Children & Schools, 37(4), 241–248. A pilot program to improve school based mental health services was instigated in one elementary school and one middle / high school. The case study followed the program from development through to implementation, documenting each step of the process.

Cowdrey, F. A. & Walz, L. (2015). Exposure therapy for fear of spiders in an adult with learning disabilities: A case report. British Journal of Learning Disabilities, 43(1), 75–82. One person was studied who had completed a pre- intervention and post- intervention questionnaire. From the results of this data the exposure therapy intervention was found to be effective in reducing the phobia. This case report highlighted a therapy that could be used to assist people with learning disabilities who also suffered from phobias.

Li, H. X., He, L., Zhang, C. C., Eisinger, R., Pan, Y. X., Wang, T., . . . Li, D. Y. (2019). Deep brain stimulation in post‐traumatic dystonia: A case series study. CNS Neuroscience & Therapeutics. 1-8. Five patients were included in the case series, all with the same condition. They all received deep brain stimulation but not in the same area of the brain. Baseline and last follow up visit were assessed with the same rating scale.

References and Further Reading  

Greenhalgh, T. (2014). How to read a paper: the basics of evidence-based medicine. (5th ed.). New York: Wiley.

Heale, R. & Twycross, A. (2018). What is a case study? Evidence Based Nursing, 21(1), 7-8.

Himmelfarb Health Sciences Library. (2019). Study design 101: case report. Retrieved from https://himmelfarb.gwu.edu/tutorials/studydesign101/casereports.cfm

Hoffmann T., Bennett S., Mar C. D. (2017). Evidence-based practice across the health professions. Chatswood, NSW: Elsevier.

Robinson, O. C., & McAdams, D. P. (2015). Four functional roles for case studies in emerging adulthood research. Emerging Adulthood, 3(6), 413-420.

• << Previous: Cross-Sectional Studies
• Next: Study Designs Home >>
• Last Updated: Jun 13, 2024 10:34 AM
• URL: https://deakin.libguides.com/quantitative-study-designs

2.2 Approaches to Research

Learning objectives.

By the end of this section, you will be able to:

• Describe the different research methods used by psychologists
• Discuss the strengths and weaknesses of case studies, naturalistic observation, surveys, and archival research
• Compare longitudinal and cross-sectional approaches to research
• Compare and contrast correlation and causation

There are many research methods available to psychologists in their efforts to understand, describe, and explain behavior and the cognitive and biological processes that underlie it. Some methods rely on observational techniques. Other approaches involve interactions between the researcher and the individuals who are being studied—ranging from a series of simple questions to extensive, in-depth interviews—to well-controlled experiments.

Each of these research methods has unique strengths and weaknesses, and each method may only be appropriate for certain types of research questions. For example, studies that rely primarily on observation produce incredible amounts of information, but the ability to apply this information to the larger population is somewhat limited because of small sample sizes. Survey research, on the other hand, allows researchers to easily collect data from relatively large samples. While this allows for results to be generalized to the larger population more easily, the information that can be collected on any given survey is somewhat limited and subject to problems associated with any type of self-reported data. Some researchers conduct archival research by using existing records. While this can be a fairly inexpensive way to collect data that can provide insight into a number of research questions, researchers using this approach have no control on how or what kind of data was collected. All of the methods described thus far are correlational in nature. This means that researchers can speak to important relationships that might exist between two or more variables of interest. However, correlational data cannot be used to make claims about cause-and-effect relationships.

Correlational research can find a relationship between two variables, but the only way a researcher can claim that the relationship between the variables is cause and effect is to perform an experiment. In experimental research, which will be discussed later in this chapter, there is a tremendous amount of control over variables of interest. While this is a powerful approach, experiments are often conducted in artificial settings. This calls into question the validity of experimental findings with regard to how they would apply in real-world settings. In addition, many of the questions that psychologists would like to answer cannot be pursued through experimental research because of ethical concerns.

Clinical or Case Studies

In 2011, the New York Times published a feature story on Krista and Tatiana Hogan, Canadian twin girls. These particular twins are unique because Krista and Tatiana are conjoined twins, connected at the head. There is evidence that the two girls are connected in a part of the brain called the thalamus, which is a major sensory relay center. Most incoming sensory information is sent through the thalamus before reaching higher regions of the cerebral cortex for processing.

Link to Learning

Watch this CBC video about Krista's and Tatiana's lives to learn more.

The implications of this potential connection mean that it might be possible for one twin to experience the sensations of the other twin. For instance, if Krista is watching a particularly funny television program, Tatiana might smile or laugh even if she is not watching the program. This particular possibility has piqued the interest of many neuroscientists who seek to understand how the brain uses sensory information.

These twins represent an enormous resource in the study of the brain, and since their condition is very rare, it is likely that as long as their family agrees, scientists will follow these girls very closely throughout their lives to gain as much information as possible (Dominus, 2011).

Over time, it has become clear that while Krista and Tatiana share some sensory experiences and motor control, they remain two distinct individuals, which provides invaluable insight for researchers interested in the mind and the brain (Egnor, 2017).

In observational research, scientists are conducting a clinical or case study when they focus on one person or just a few individuals. Indeed, some scientists spend their entire careers studying just 10–20 individuals. Why would they do this? Obviously, when they focus their attention on a very small number of people, they can gain a precious amount of insight into those cases. The richness of information that is collected in clinical or case studies is unmatched by any other single research method. This allows the researcher to have a very deep understanding of the individuals and the particular phenomenon being studied.

If clinical or case studies provide so much information, why are they not more frequent among researchers? As it turns out, the major benefit of this particular approach is also a weakness. As mentioned earlier, this approach is often used when studying individuals who are interesting to researchers because they have a rare characteristic. Therefore, the individuals who serve as the focus of case studies are not like most other people. If scientists ultimately want to explain all behavior, focusing attention on such a special group of people can make it difficult to generalize any observations to the larger population as a whole. Generalizing refers to the ability to apply the findings of a particular research project to larger segments of society. Again, case studies provide enormous amounts of information, but since the cases are so specific, the potential to apply what’s learned to the average person may be very limited.

Naturalistic Observation

If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances are that almost everyone in the classroom will raise their hand, but do you think hand washing after every trip to the restroom is really that universal?

This is very similar to the phenomenon mentioned earlier in this chapter: many individuals do not feel comfortable answering a question honestly. But if we are committed to finding out the facts about hand washing, we have other options available to us.

Suppose we send a classmate into the restroom to actually watch whether everyone washes their hands after using the restroom. Will our observer blend into the restroom environment by wearing a white lab coat, sitting with a clipboard, and staring at the sinks? We want our researcher to be inconspicuous—perhaps standing at one of the sinks pretending to put in contact lenses while secretly recording the relevant information. This type of observational study is called naturalistic observation : observing behavior in its natural setting. To better understand peer exclusion, Suzanne Fanger collaborated with colleagues at the University of Texas to observe the behavior of preschool children on a playground. How did the observers remain inconspicuous over the duration of the study? They equipped a few of the children with wireless microphones (which the children quickly forgot about) and observed while taking notes from a distance. Also, the children in that particular preschool (a “laboratory preschool”) were accustomed to having observers on the playground (Fanger, Frankel, & Hazen, 2012).

It is critical that the observer be as unobtrusive and as inconspicuous as possible: when people know they are being watched, they are less likely to behave naturally. If you have any doubt about this, ask yourself how your driving behavior might differ in two situations: In the first situation, you are driving down a deserted highway during the middle of the day; in the second situation, you are being followed by a police car down the same deserted highway ( Figure 2.7 ).

It should be pointed out that naturalistic observation is not limited to research involving humans. Indeed, some of the best-known examples of naturalistic observation involve researchers going into the field to observe various kinds of animals in their own environments. As with human studies, the researchers maintain their distance and avoid interfering with the animal subjects so as not to influence their natural behaviors. Scientists have used this technique to study social hierarchies and interactions among animals ranging from ground squirrels to gorillas. The information provided by these studies is invaluable in understanding how those animals organize socially and communicate with one another. The anthropologist Jane Goodall , for example, spent nearly five decades observing the behavior of chimpanzees in Africa ( Figure 2.8 ). As an illustration of the types of concerns that a researcher might encounter in naturalistic observation, some scientists criticized Goodall for giving the chimps names instead of referring to them by numbers—using names was thought to undermine the emotional detachment required for the objectivity of the study (McKie, 2010).

The greatest benefit of naturalistic observation is the validity , or accuracy, of information collected unobtrusively in a natural setting. Having individuals behave as they normally would in a given situation means that we have a higher degree of ecological validity, or realism, than we might achieve with other research approaches. Therefore, our ability to generalize the findings of the research to real-world situations is enhanced. If done correctly, we need not worry about people or animals modifying their behavior simply because they are being observed. Sometimes, people may assume that reality programs give us a glimpse into authentic human behavior. However, the principle of inconspicuous observation is violated as reality stars are followed by camera crews and are interviewed on camera for personal confessionals. Given that environment, we must doubt how natural and realistic their behaviors are.

The major downside of naturalistic observation is that they are often difficult to set up and control. In our restroom study, what if you stood in the restroom all day prepared to record people’s hand washing behavior and no one came in? Or, what if you have been closely observing a troop of gorillas for weeks only to find that they migrated to a new place while you were sleeping in your tent? The benefit of realistic data comes at a cost. As a researcher you have no control of when (or if) you have behavior to observe. In addition, this type of observational research often requires significant investments of time, money, and a good dose of luck.

Sometimes studies involve structured observation. In these cases, people are observed while engaging in set, specific tasks. An excellent example of structured observation comes from Strange Situation by Mary Ainsworth (you will read more about this in the chapter on lifespan development). The Strange Situation is a procedure used to evaluate attachment styles that exist between an infant and caregiver. In this scenario, caregivers bring their infants into a room filled with toys. The Strange Situation involves a number of phases, including a stranger coming into the room, the caregiver leaving the room, and the caregiver’s return to the room. The infant’s behavior is closely monitored at each phase, but it is the behavior of the infant upon being reunited with the caregiver that is most telling in terms of characterizing the infant’s attachment style with the caregiver.

Another potential problem in observational research is observer bias . Generally, people who act as observers are closely involved in the research project and may unconsciously skew their observations to fit their research goals or expectations. To protect against this type of bias, researchers should have clear criteria established for the types of behaviors recorded and how those behaviors should be classified. In addition, researchers often compare observations of the same event by multiple observers, in order to test inter-rater reliability : a measure of reliability that assesses the consistency of observations by different observers.

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally ( Figure 2.9 ). Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.

Surveys allow researchers to gather data from larger samples than may be afforded by other research methods . A sample is a subset of individuals selected from a population , which is the overall group of individuals that the researchers are interested in. Researchers study the sample and seek to generalize their findings to the population. Generally, researchers will begin this process by calculating various measures of central tendency from the data they have collected. These measures provide an overall summary of what a typical response looks like. There are three measures of central tendency: mode, median, and mean. The mode is the most frequently occurring response, the median lies at the middle of a given data set, and the mean is the arithmetic average of all data points. Means tend to be most useful in conducting additional analyses like those described below; however, means are very sensitive to the effects of outliers, and so one must be aware of those effects when making assessments of what measures of central tendency tell us about a data set in question.

There is both strength and weakness of the survey in comparison to case studies. By using surveys, we can collect information from a larger sample of people. A larger sample is better able to reflect the actual diversity of the population, thus allowing better generalizability. Therefore, if our sample is sufficiently large and diverse, we can assume that the data we collect from the survey can be generalized to the larger population with more certainty than the information collected through a case study. However, given the greater number of people involved, we are not able to collect the same depth of information on each person that would be collected in a case study.

Another potential weakness of surveys is something we touched on earlier in this chapter: People don't always give accurate responses. They may lie, misremember, or answer questions in a way that they think makes them look good. For example, people may report drinking less alcohol than is actually the case.

Any number of research questions can be answered through the use of surveys. One real-world example is the research conducted by Jenkins, Ruppel, Kizer, Yehl, and Griffin (2012) about the backlash against the US Arab-American community following the terrorist attacks of September 11, 2001. Jenkins and colleagues wanted to determine to what extent these negative attitudes toward Arab-Americans still existed nearly a decade after the attacks occurred. In one study, 140 research participants filled out a survey with 10 questions, including questions asking directly about the participant’s overt prejudicial attitudes toward people of various ethnicities. The survey also asked indirect questions about how likely the participant would be to interact with a person of a given ethnicity in a variety of settings (such as, “How likely do you think it is that you would introduce yourself to a person of Arab-American descent?”). The results of the research suggested that participants were unwilling to report prejudicial attitudes toward any ethnic group. However, there were significant differences between their pattern of responses to questions about social interaction with Arab-Americans compared to other ethnic groups: they indicated less willingness for social interaction with Arab-Americans compared to the other ethnic groups. This suggested that the participants harbored subtle forms of prejudice against Arab-Americans, despite their assertions that this was not the case (Jenkins et al., 2012).

Archival Research

Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research . Archival research relies on looking at past records or data sets to look for interesting patterns or relationships.

For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and calculate how long it took them to complete their degrees, as well as course loads, grades, and extracurricular involvement. Archival research could provide important information about who is most likely to complete their education, and it could help identify important risk factors for struggling students ( Figure 2.10 ).

In comparing archival research to other research methods, there are several important distinctions. For one, the researcher employing archival research never directly interacts with research participants. Therefore, the investment of time and money to collect data is considerably less with archival research. Additionally, researchers have no control over what information was originally collected. Therefore, research questions have to be tailored so they can be answered within the structure of the existing data sets. There is also no guarantee of consistency between the records from one source to another, which might make comparing and contrasting different data sets problematic.

Longitudinal and Cross-Sectional Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again at age 40.

Another approach is cross-sectional research. In cross-sectional research , a researcher compares multiple segments of the population at the same time. Using the dietary habits example above, the researcher might directly compare different groups of people by age. Instead of studying a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old individuals. While cross-sectional research requires a shorter-term investment, it is also limited by differences that exist between the different generations (or cohorts) that have nothing to do with age per se, but rather reflect the social and cultural experiences of different generations of individuals that make them different from one another.

To illustrate this concept, consider the following survey findings. In recent years there has been significant growth in the popular support of same-sex marriage. Many studies on this topic break down survey participants into different age groups. In general, younger people are more supportive of same-sex marriage than are those who are older (Jones, 2013). Does this mean that as we age we become less open to the idea of same-sex marriage, or does this mean that older individuals have different perspectives because of the social climates in which they grew up? Longitudinal research is a powerful approach because the same individuals are involved in the research project over time, which means that the researchers need to be less concerned with differences among cohorts affecting the results of their study.

Often longitudinal studies are employed when researching various diseases in an effort to understand particular risk factors. Such studies often involve tens of thousands of individuals who are followed for several decades. Given the enormous number of people involved in these studies, researchers can feel confident that their findings can be generalized to the larger population. The Cancer Prevention Study-3 (CPS-3) is one of a series of longitudinal studies sponsored by the American Cancer Society aimed at determining predictive risk factors associated with cancer. When participants enter the study, they complete a survey about their lives and family histories, providing information on factors that might cause or prevent the development of cancer. Then every few years the participants receive additional surveys to complete. In the end, hundreds of thousands of participants will be tracked over 20 years to determine which of them develop cancer and which do not.

Clearly, this type of research is important and potentially very informative. For instance, earlier longitudinal studies sponsored by the American Cancer Society provided some of the first scientific demonstrations of the now well-established links between increased rates of cancer and smoking (American Cancer Society, n.d.) ( Figure 2.11 ).

As with any research strategy, longitudinal research is not without limitations. For one, these studies require an incredible time investment by the researcher and research participants. Given that some longitudinal studies take years, if not decades, to complete, the results will not be known for a considerable period of time. In addition to the time demands, these studies also require a substantial financial investment. Many researchers are unable to commit the resources necessary to see a longitudinal project through to the end.

Research participants must also be willing to continue their participation for an extended period of time, and this can be problematic. People move, get married and take new names, get ill, and eventually die. Even without significant life changes, some people may simply choose to discontinue their participation in the project. As a result, the attrition rates, or reduction in the number of research participants due to dropouts, in longitudinal studies are quite high and increase over the course of a project. For this reason, researchers using this approach typically recruit many participants fully expecting that a substantial number will drop out before the end. As the study progresses, they continually check whether the sample still represents the larger population, and make adjustments as necessary.

As an Amazon Associate we earn from qualifying purchases.

This book may not be used in the training of large language models or otherwise be ingested into large language models or generative AI offerings without OpenStax's permission.

Want to cite, share, or modify this book? This book uses the Creative Commons Attribution License and you must attribute OpenStax.

Access for free at https://openstax.org/books/psychology-2e/pages/1-introduction

• Authors: Rose M. Spielman, William J. Jenkins, Marilyn D. Lovett
• Publisher/website: OpenStax
• Book title: Psychology 2e
• Publication date: Apr 22, 2020
• Location: Houston, Texas
• Book URL: https://openstax.org/books/psychology-2e/pages/1-introduction
• Section URL: https://openstax.org/books/psychology-2e/pages/2-2-approaches-to-research

© Jan 6, 2024 OpenStax. Textbook content produced by OpenStax is licensed under a Creative Commons Attribution License . The OpenStax name, OpenStax logo, OpenStax book covers, OpenStax CNX name, and OpenStax CNX logo are not subject to the Creative Commons license and may not be reproduced without the prior and express written consent of Rice University.

Observational vs. Experimental Study: A Comprehensive Guide

Explore the fundamental disparities between experimental and observational studies in this comprehensive guide by Santos Research Center, Corp. Uncover concepts such as control group, random sample, cohort studies, response variable, and explanatory variable that shape the foundation of these methodologies. Discover the significance of randomized controlled trials and case control studies, examining causal relationships and the role of dependent variables and independent variables in research designs.

This enlightening exploration also delves into the meticulous scientific study process, involving survey members, systematic reviews, and statistical analyses. Investigate the careful balance of control group and treatment group dynamics, highlighting how researchers meticulously assign variables and analyze statistical patterns to discern meaningful insights. From dissecting issues like lung cancer to understanding sleep patterns, this guide emphasizes the precision of controlled experiments and controlled trials, where variables are isolated and scrutinized, paving the way for a deeper comprehension of the world through empirical research.

Introduction to Observational and Experimental Studies

These two studies are the cornerstones of scientific inquiry, each offering a distinct approach to unraveling the mysteries of the natural world.

Observational studies allow us to observe, document, and gather data without direct intervention. They provide a means to explore real-world scenarios and trends, making them valuable when manipulating variables is not feasible or ethical. From surveys to meticulous observations, these studies shed light on existing conditions and relationships.

Experimental studies , in contrast, put researchers in the driver's seat. They involve the deliberate manipulation of variables to understand their impact on specific outcomes. By controlling the conditions, experimental studies establish causal relationships, answering questions of causality with precision. This approach is pivotal for hypothesis testing and informed decision-making.

At Santos Research Center, Corp., we recognize the importance of both observational and experimental studies. We employ these methodologies in our diverse research projects to ensure the highest quality of scientific investigation and to answer a wide range of research questions.

Observational Studies: A Closer Look

In our exploration of research methodologies, let's zoom in on observational research studies—an essential facet of scientific inquiry that we at Santos Research Center, Corp., expertly employ in our diverse research projects.

What is an Observational Study?

Observational research studies involve the passive observation of subjects without any intervention or manipulation by researchers. These studies are designed to scrutinize the relationships between variables and test subjects, uncover patterns, and draw conclusions grounded in real-world data.

Researchers refrain from interfering with the natural course of events in controlled experiment. Instead, they meticulously gather data by keenly observing and documenting information about the test subjects and their surroundings. This approach permits the examination of variables that cannot be ethically or feasibly manipulated, making it particularly valuable in certain research scenarios.

Types of Observational Studies

Now, let's delve into the various forms that observational studies can take, each with its distinct characteristics and applications.

Cohort Studies:  A cohort study is a type of observational study that entails tracking one group of individuals over an extended period. Its primary goal is to identify potential causes or risk factors for specific outcomes or treatment group. Cohort studies provide valuable insights into the development of conditions or diseases and the factors that influence them.

Case-Control Studies:  Case-control studies, on the other hand, involve the comparison of individuals with a particular condition or outcome to those without it (the control group). These studies aim to discern potential causal factors or associations that may have contributed to the development of the condition under investigation.

Cross-Sectional Studies:  Cross-sectional studies take a snapshot of a diverse group of individuals at a single point in time. By collecting data from this snapshot, researchers gain insights into the prevalence of a specific condition or the relationships between variables at that precise moment. Cross-sectional studies are often used to assess the health status of the different groups within a population or explore the interplay between various factors.

Advantages and Limitations of Observational Studies

Observational studies, as we've explored, are a vital pillar of scientific research, offering unique insights into real-world phenomena. In this section, we will dissect the advantages and limitations that characterize these studies, shedding light on the intricacies that researchers grapple with when employing this methodology.

Advantages: One of the paramount advantages of observational studies lies in their utilization of real-world data. Unlike controlled experiments that operate in artificial settings, observational studies embrace the complexities of the natural world. This approach enables researchers to capture genuine behaviors, patterns, and occurrences as they unfold. As a result, the data collected reflects the intricacies of real-life scenarios, making it highly relevant and applicable to diverse settings and populations.

Moreover, in a randomized controlled trial, researchers looked to randomly assign participants to a group. Observational studies excel in their capacity to examine long-term trends. By observing one group of subjects over extended periods, research scientists gain the ability to track developments, trends, and shifts in behavior or outcomes. This longitudinal perspective is invaluable when studying phenomena that evolve gradually, such as chronic diseases, societal changes, or environmental shifts. It allows for the detection of subtle nuances that may be missed in shorter-term investigations.

Limitations: However, like any research methodology, observational studies are not without their limitations. One significant challenge of statistical study lies in the potential for biases. Since researchers do not intervene in the subjects' experiences, various biases can creep into the data collection process. These biases may arise from participant self-reporting, observer bias, or selection bias in random sample, among others. Careful design and rigorous data analysis are crucial for mitigating these biases.

Another limitation is the presence of confounding variables. In observational studies, it can be challenging to isolate the effect of a specific variable from the myriad of other factors at play. These confounding variables can obscure the true relationship between the variables of interest, making it difficult to establish causation definitively. Research scientists must employ statistical techniques to control for or adjust these confounding variables.

Additionally, observational studies face constraints in their ability to establish causation. While they can identify associations and correlations between variables, they cannot prove causality or causal relationship. Establishing causation typically requires controlled experiments where researchers can manipulate independent variables systematically. In observational studies, researchers can only infer potential causation based on the observed associations.

Experimental Studies: Delving Deeper

In the intricate landscape of scientific research, we now turn our gaze toward experimental studies—a dynamic and powerful method that Santos Research Center, Corp. skillfully employs in our pursuit of knowledge.

What is an Experimental Study?

While some studies observe and gather data passively, experimental studies take a more proactive approach. Here, researchers actively introduce an intervention or treatment to an experiment group study its effects on one or more variables. This methodology empowers researchers to manipulate independent variables deliberately and examine their direct impact on dependent variables.

Experimental research are distinguished by their exceptional ability to establish cause-and-effect relationships. This invaluable characteristic allows researchers to unlock the mysteries of how one variable influences another, offering profound insights into the scientific questions at hand. Within the controlled environment of an experimental study, researchers can systematically test hypotheses, shedding light on complex phenomena.

Key Features of Experimental Studies

Central to statistical analysis, the rigor and reliability of experimental studies are several key features that ensure the validity of their findings.

Randomized Controlled Trials:  Randomization is a critical element in experimental studies, as it ensures that subjects are assigned to groups in a random assignment. This randomly assigned allocation minimizes the risk of unintentional biases and confounding variables, strengthening the credibility of the study's outcomes.

Control Groups:  Control groups play a pivotal role in experimental studies by serving as a baseline for comparison. They enable researchers to assess the true impact of the intervention being studied. By comparing the outcomes of the intervention group to those of survey members of the control group, researchers can discern whether the intervention caused the observed changes.

Blinding:  Both single-blind and double-blind techniques are employed in experimental studies to prevent biases from influencing the study or controlled trial's outcomes. Single-blind studies keep either the subjects or the researchers unaware of certain aspects of the study, while double-blind studies extend this blindness to both parties, enhancing the objectivity of the study.

These key features work in concert to uphold the integrity and trustworthiness of the results generated through experimental studies.

Advantages and Limitations of Experimental Studies

As with any research methodology, this one comes with its unique set of advantages and limitations.

Advantages:  These studies offer the distinct advantage of establishing causal relationships between two or more variables together. The controlled environment allows researchers to exert authority over variables, ensuring that changes in the dependent variable can be attributed to the independent variable. This meticulous control results in high-quality, reliable data that can significantly contribute to scientific knowledge.

Limitations:  However, experimental ones are not without their challenges. They may raise ethical concerns, particularly when the interventions involve potential risks to subjects. Additionally, their controlled nature can limit their real-world applicability, as the conditions in experiments may not accurately mirror those in the natural world. Moreover, executing an experimental study in randomized controlled, often demands substantial resources, with other variables including time, funding, and personnel.

Observational vs Experimental: A Side-by-Side Comparison

Having previously examined observational and experimental studies individually, we now embark on a side-by-side comparison to illuminate the key distinctions and commonalities between these foundational research approaches.

Key Differences and Notable Similarities

Methodologies

• Observational Studies : Characterized by passive observation, where researchers collect data without direct intervention, allowing the natural course of events to unfold.
• Experimental Studies : Involve active intervention, where researchers deliberately manipulate variables to discern their impact on specific outcomes, ensuring control over the experimental conditions.
• Observational Studies : Designed to identify patterns, correlations, and associations within existing data, shedding light on relationships within real-world settings.
• Experimental Studies : Geared toward establishing causality by determining the cause-and-effect relationships between variables, often in controlled laboratory environments.
• Observational Studies : Yield real-world data, reflecting the complexities and nuances of natural phenomena.
• Experimental Studies : Generate controlled data, allowing for precise analysis and the establishment of clear causal connections.

Observational studies excel at exploring associations and uncovering patterns within the intricacies of real-world settings, while experimental studies shine as the gold standard for discerning cause-and-effect relationships through meticulous control and manipulation in controlled environments. Understanding these differences and similarities empowers researchers to choose the most appropriate method for their specific research objectives.

When to Use Which: Practical Applications

The decision to employ either observational or experimental studies hinges on the research objectives at hand and the available resources. Observational studies prove invaluable when variable manipulation is impractical or ethically challenging, making them ideal for delving into long-term trends and uncovering intricate associations between certain variables (response variable or explanatory variable). On the other hand, experimental studies emerge as indispensable tools when the aim is to definitively establish causation and methodically control variables.

At Santos Research Center, Corp., our approach to both scientific study and methodology is characterized by meticulous consideration of the specific research goals. We recognize that the quality of outcomes hinges on selecting the most appropriate method of research study. Our unwavering commitment to employing both observational and experimental research studies further underscores our dedication to advancing scientific knowledge across diverse domains.

Conclusion: The Synergy of Experimental and Observational Studies in Research

In conclusion, both observational and experimental studies are integral to scientific research, offering complementary approaches with unique strengths and limitations. At Santos Research Center, Corp., we leverage these methodologies to contribute meaningfully to the scientific community.

Explore our projects and initiatives at Santos Research Center, Corp. by visiting our website or contacting us at (813) 249-9100, where our unwavering commitment to rigorous research practices and advancing scientific knowledge awaits.

Recent Posts

Learn everything about Respiratory Syncytial Virus (RSV), from symptoms and diagnosis to treatment and prevention. Stay informed and protect your health with...

Discover key insights on Alzheimer's disease, including symptoms, stages, and care tips. Learn how to manage the condition and find out how you can...

Discover expert insights on migraines, from symptoms and causes to management strategies, and learn about our specialized support at Santos Research Center.

Explore our in-depth guide on UTIs, covering everything from symptoms and causes to effective treatments, and learn how to manage and prevent urinary tract infections.

Your definitive guide to COVID symptoms. Dive deep into the signs of COVID-19, understand the new variants, and get answers to your most pressing questions.

Unravel the differences between observational and experimental studies. Dive into the intricacies of each method and discover their unique applications in research.

Discover the different types of clinical trials and their significance in advancing medical science. Dive deep into the world of clinical research with Santos Research Center.

Santos Research Center, Corp. is a research facility conducting paid clinical trials, in partnership with major pharmaceutical companies & CROs. We work with patients from across the Tampa Bay area.

Contact Details

Navigation menu.

Live revision! Join us for our free exam revision livestreams Watch now →

Reference Library

Collections

• See what's new
• All Resources
• Student Resources
• Assessment Resources
• Teaching Resources
• CPD Courses
• Livestreams

Study notes, videos, interactive activities and more!

Psychology news, insights and enrichment

Currated collections of free resources

Browse resources by topic

• All Psychology Resources

Resource Selections

Currated lists of resources

Study Notes

Types of Experiment: Overview

Last updated 6 Sept 2022

• Share on Facebook
• Share on Twitter
• Share by Email

Different types of methods are used in research, which loosely fall into 1 of 2 categories.

Experimental (Laboratory, Field & Natural) & N on experimental ( correlations, observations, interviews, questionnaires and case studies).

All the three types of experiments have characteristics in common. They all have:

• an independent variable (I.V.) which is manipulated or a naturally occurring variable
• a dependent variable (D.V.) which is measured
• there will be at least two conditions in which participants produce data.

Note – natural and quasi experiments are often used synonymously but are not strictly the same, as with quasi experiments participants cannot be randomly assigned, so rather than there being a condition there is a condition.

Laboratory Experiments

These are conducted under controlled conditions, in which the researcher deliberately changes something (I.V.) to see the effect of this on something else (D.V.).

Control – lab experiments have a high degree of control over the environment & other extraneous variables which means that the researcher can accurately assess the effects of the I.V, so it has higher internal validity.

Replicable – due to the researcher’s high levels of control, research procedures can be repeated so that the reliability of results can be checked.

Limitations

Lacks ecological validity – due to the involvement of the researcher in manipulating and controlling variables, findings cannot be easily generalised to other (real life) settings, resulting in poor external validity.

Field Experiments

These are carried out in a natural setting, in which the researcher manipulates something (I.V.) to see the effect of this on something else (D.V.).

Validity – field experiments have some degree of control but also are conducted in a natural environment, so can be seen to have reasonable internal and external validity.

Less control than lab experiments and therefore extraneous variables are more likely to distort findings and so internal validity is likely to be lower.

Natural / Quasi Experiments

These are typically carried out in a natural setting, in which the researcher measures the effect of something which is to see the effect of this on something else (D.V.). Note that in this case there is no deliberate manipulation of a variable; this already naturally changing, which means the research is merely measuring the effect of something that is already happening.

High ecological validity – due to the lack of involvement of the researcher; variables are naturally occurring so findings can be easily generalised to other (real life) settings, resulting in high external validity.

Lack of control – natural experiments have no control over the environment & other extraneous variables which means that the researcher cannot always accurately assess the effects of the I.V, so it has low internal validity.

Not replicable – due to the researcher’s lack of control, research procedures cannot be repeated so that the reliability of results cannot be checked.

• Laboratory Experiment
• Field experiment
• Quasi Experiment
• Natural Experiment
• Field experiments

You might also like

Field experiments, laboratory experiments, natural experiments, control of extraneous variables, similarities and differences between classical and operant conditioning, learning approaches - social learning theory, differences between behaviourism and social learning theory, ​research methods in the social learning theory, our subjects.

• › Criminology
• › Economics
• › Geography
• › Health & Social Care
• › Psychology
• › Sociology
• › Teaching & learning resources
• › Student revision workshops
• › Online student courses
• › CPD for teachers
• › Livestreams
• › Teaching jobs

Boston House, 214 High Street, Boston Spa, West Yorkshire, LS23 6AD Tel: 01937 848885

• › Contact us
• › Terms of use
• › Privacy & cookies

© 2002-2024 Tutor2u Limited. Company Reg no: 04489574. VAT reg no 816865400.

Register Now

Confirm Password *

Terms * By registering, you agree to the Terms of Service and Privacy Policy .

Lost Password

Lost your password? Please enter your email address. You will receive a link and will create a new password via email.

Q&A Platform

Difference between case study and experiment.

• Difference Between a White Paper and a Case Study
• Difference Between Case Study and Survey

Answer ( 1 )

😃 Are you curious to know the difference between a case study and an experiment? If so, you’ve come to the right place!

A case study is a detailed examination of a particular situation. It typically includes a comprehensive review of relevant information, such as data, documents, interviews, surveys, and observations. It’s often used to gain insight into complex problems and learn more about a particular event or phenomenon.

An experiment, on the other hand, is a procedure in which a hypothesis is tested. It typically involves manipulation of variables, collection of data, and analysis of the results. The goal is to find out if the hypothesis is true or false.

The key difference between a case study and an experiment is that a case study is descriptive in nature, while an experiment is designed to test a hypothesis. A case study does not involve manipulating variables or testing a hypothesis; rather, it is used to gain insight into an event or phenomenon.

In addition, a case study is typically conducted over a longer period of time, while an experiment is usually conducted over a shorter period of time. Moreover, a case study is often used to examine a single event or phenomenon, while an experiment is typically used to test a hypothesis across a variety of different situations and conditions.

To sum it up, the difference between a case study and an experiment is that a case study is a descriptive study of a particular situation, while an experiment is a procedure in which a hypothesis is tested. Both methods can be used to gain insight into complex problems and learn more about a particular event or phenomenon.

So, next time you’re trying to decide between a case study and an experiment, remember the key difference between the two! 🤓

Leave an answer

You must login or register to add a new answer .

 Previous question

Next question 

Get the Reddit app

A subreddit dedicated to PhDs.

What are the TRUE differences between case studies and experimental research?

Hi guys, I am a newbie Ph.D. student in the education field.

I bring a question about case studies.

Here I got a brief explanation of what is a case study and experimental research, from google.

"Case studies are a prospective or retrospective deep dive into a single case, used a lot in business, education, and perhaps also law, medicine (more often retrospective) or other fields. Experimental research involves comparisons of variables under manipulated conditions. It is always prospective and used most often in science but also in education, medicine or other fields. It involves testing a hypothesis with the scientific method and rejecting or failing to reject the hypothesis."

However, in the education field, we can see a lot of case studies having a control group / experimental group as same as the experimental research. Also, in those case studies, the participants are not scarce. Also, those case studies have research questions starting with "is .... effective....?" which is the same as the experimental research.

I am so confused. What is exactly a case study and what are the true differences between experimental research?? I really want to differentiate between those two research designs. I look forward to having your comments!

• Find an Expert
• Site Endowment

Understanding clinical studies

Revised 2014

What are clinical trials?

Randomized controlled trial, cohort studies, case-control studies, fact sheets/booklets.

Hormonal Contraception

Embryo donation: what should i know, fertility options after vasectomy.

Assisted Reproductive Technologies (booklet)

Resources for you.

Fertility in the News

State and Territory Infertility Insurance Laws

Fact Sheets and Infographics

Reproductive Rights and You

Patient Journeys

Frequently Asked Questions

Reproductive Topics

SART Fertility Experts Podcast

Patient Education Videos

Terms and Definitions

Patient Stories

Find a Health Professional

How IBM helps Wimbledon use generative AI to drive personalised fan engagement

This collaboration with Wimbledon teams extends beyond the fan-facing digital platform, into enterprise-wide transformation.

Top 7 risks to your identity security posture

5 min read - Identity misconfigurations and blind spots stand out as critical concerns that undermine an organization’s identity security posture.

Intesa Sanpaolo and IBM secure digital transactions with fully homomorphic encryption

6 min read - Explore how European bank Intesa Sanpaolo and IBM partnered to deliver secure digital transactions using fully homomorphic encryption.

What is AI risk management?

8 min read - AI risk management is the process of identifying, mitigating and addressing the potential risks associated with AI technologies.

How IBM and AWS are partnering to deliver the promise of responsible AI

4 min read - This partnership between IBM and Amazon SageMaker is poised to play a pivotal role in shaping responsible AI practices across industries

June 26, 2024

A major upgrade to Db2® Warehouse on IBM Cloud®

June 25, 2024

Increase efficiency in asset lifecycle management with Maximo Application Suite’s new AI-power...

Achieving operational efficiency through Instana’s Intelligent Remediation

June 24, 2024

Manage the routing of your observability log and event data 

June 21, 2024

IBM unveils Cloud Pak for Data 5.0

Best practices for augmenting human intelligence with AI

2 min read - Enabling participation in the AI-driven economy to be underpinned by fairness, transparency, explainability, robustness and privacy. 

Microcontrollers vs. microprocessors: What’s the difference?

6 min read - Microcontroller units (MCUs) and microprocessor units (MPUs) are two kinds of integrated circuits that, while similar in certain ways, are very different in many others.

Mastering budget control in the age of AI: Leveraging on-premises and cloud XaaS for success 

2 min read - As organizations harness the power of AI while controlling costs, leveraging anything as a service (XaaS) models emerges as strategic.

Highlights by topic

Use IBM Watsonx’s AI or build your own machine learning models

Automate IT infrastructure management

Cloud-native software to secure resources and simplify compliance

Run code on real quantum systems using a full-stack SDK

Aggregate and analyze large datasets

Store, query and analyze structured data

Manage infrastructure, environments and deployments

Run workloads on hybrid cloud infrastructure

Responsible AI can revolutionize tax agencies to improve citizen services

Generative AI can revolutionize tax administration and drive toward a more personalized and ethical future.

Speed, scale and trustworthy AI on IBM Z with Machine Learning for IBM z/OS v3.2 

4 min read - Machine Learning for IBM® z/OS® is an AI platform made for IBM z/OS environments, combining data and transaction gravity with AI infusion.

The recipe for RAG: How cloud services enable generative AI outcomes across industries

4 min read - While the AI is the key component of the RAG framework, other “ingredients” such as PaaS solutions are integral to the mix

Rethink IT spend in the age of generative AI

3 min read - It's critical for organizations to consider frameworks like FinOps and TBM for visibility and accountability of all tech expenditure.

6 hard truths CEOs must confront in the generative AI era

5 min read - A call to action for CEOs to confront the realities of generative AI and to seize its potential for your organization.

Immutable backup strategies with cloud storage

4 min read - IBM Cloud Object Storage is a versatile and scalable solution that is crucial for storing and protecting data backups.

T-Mobile unlocks marketing efficiency with Adobe Workfront

4 min read - Discover how the T-Mobile team creates a more seamless work management system for its content supply chain with Adobe and IBM Consulting.

IBM Newsletters

  Southern African Linguistics and Applied Language Studies Journal / Southern African Linguistics and Applied Language Studies / Vol. 42 No. 2 (2024) / Articles (function() { function async_load(){ var s = document.createElement('script'); s.type = 'text/javascript'; s.async = true; var theUrl = 'https://www.journalquality.info/journalquality/ratings/2406-www-ajol-info-salas'; s.src = theUrl + ( theUrl.indexOf("?") >= 0 ? "&" : "?") + 'ref=' + encodeURIComponent(window.location.href); var embedder = document.getElementById('jpps-embedder-ajol-salas'); embedder.parentNode.insertBefore(s, embedder); } if (window.attachEvent) window.attachEvent('onload', async_load); else window.addEventListener('load', async_load, false); })();

Article sidebar, article details, main article content, cultural and social construction of illness: the case of basotho patients’ folk interpretations of their illness experiences, raphael thuube, beatrice ekanjume.

This article demonstrates the role played by culture in shaping the individual’s construction of the meaning and experience of illness. It  shows how culture plays a significant part in providing valuable insights into an individual’s lived experiences and their perceptions of  what constitutes their physical, psychological and/or emotional afflictions. It reveals that Basotho patients express cultural beliefs  through idiomatic forms which merely allude to the real nature of their illness(es), and some Sesotho vocabulary that may be difficult to  understand, especially when talking about sexually transmitted illnesses or conditions. The results show that cultural differences and  taboo topics surrounding sexuality were a major cause of the communication barriers between patients and health care professionals.  The article highlights that the cultural and social constructions of the people’s illness experiences offer a valuable window into the unique  design and complex nature of their value and belief systems that shape their everyday behaviours and constructions of and reactions to illness. It argues that these value and belief systems have the potential to yield significant insights into the nature or essence  of the patients’ cultural explanatory representations of their illness experiences. The article fills the gap that exists vis-a-vis the impact of  subjective experiences and social constructions of health and illness among Basotho adults. 

AJOL is a Non Profit Organisation that cannot function without donations. AJOL and the millions of African and international researchers who rely on our free services are deeply grateful for your contribution. AJOL is annually audited and was also independently assessed in 2019 by E&Y.

Your donation is guaranteed to directly contribute to Africans sharing their research output with a global readership.

• For annual AJOL Supporter contributions, please view our Supporters page.

Journal Identifiers