| Feature | Case Study | Experiment |
|---|---|---|
| Sample Size | Usually or a very small group | Large groups for statistical power |
| Control | Low control over variables | High control over extraneous variables |
| Goal | In-depth description and insight | Establishing cause-and-effect |
| Setting | Naturalistic/Real-life context | Often artificial/Laboratory setting |
Unlike experiments, case studies do not typically involve the manipulation of an Independent Variable (IV); instead, they observe naturally occurring conditions.
Evaluate Validity: When asked to evaluate case studies, always mention high ecological validity because they study real-life behavior in its natural context.
Address Generalizability: A common exam point is the lack of population validity; because the sample is unique, findings may not apply to the wider population ( problem).
Identify the Method: If a scenario describes a researcher following one person for ten years using multiple tests, identify it as a longitudinal case study.
Check for Bias: Always consider the 'researcher-participant relationship'; long-term contact can lead to a loss of objectivity, which reduces the scientific rigor of the data.
A common misconception is that case studies are purely qualitative; in reality, they frequently incorporate quantitative clinical data to support their findings.
Students often confuse case studies with simple observations; remember that a case study is a methodological framework that includes observations, but is not limited to them.
Another pitfall is assuming that case studies can prove causation; while they provide strong hints, the lack of controlled variables means they can only suggest correlations or provide descriptive insights.