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Distinguish between observational studies and experiments, and understand causation vs. association.
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Observational Study
Experiment
Confounding Variables (Lurking Variables)
Without random assignment:
A researcher records the average daily coffee consumption and sleep hours for 100 people. She finds that people who drink more coffee sleep fewer hours. Can she conclude that coffee causes reduced sleep? Explain.
No, she cannot conclude causation. This is an observational study — data is collected without imposing a treatment. The researcher simply observes existing behaviors.
Confounding variables may explain the relationship:
The correlation observed doesn't prove causation. To conclude that coffee causes sleep reduction, you'd need a where people are randomly assigned to drink coffee or not, with other factors held equal.
Avoid these 3 frequent errors
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With random assignment:
Cohort Study (Observational)
Case-Control Study (Observational)
Randomized Controlled Trial (RCT) (Experiment)
Need causal inference? → Must use random assignment Only have observational data? → Report association, NOT causation; identify potential confounders
Always distinguish between "associated with" (observational) and "causes" (experimental). If a study lacks random assignment, you cannot conclude causation no matter how strong the association.
In a pharmaceutical trial, some patients receive a new drug while others receive a placebo, randomly assigned. Both groups are followed for 6 months. Is this observational or experimental? Identify the treatment, response variable, and control group.
Type: This is an EXPERIMENT (also called a Randomized Controlled Trial or RCT).
Why? The researcher actively assigns a treatment (new drug vs. placebo) through random assignment, rather than just observing.
Components:
Treatment (Explanatory Variable): Type of pill — either the new drug or placebo
Response Variable: Outcome measured — likely symptom improvement, side effects, or recovery time over 6 months
Experimental Group: Patients receiving the new drug
Control Group: Patients receiving the placebo
Random Assignment: Crucial for validity — ensures the treatment groups are comparable. Without it, we can't isolate the drug's effect from other differences.
Key advantage: Random assignment minimizes confounding variables, making causation conclusions possible.
Design either an observational study or experiment to investigate whether a new study app improves student exam scores. Clearly state which you'd choose and justify your choice.
Best choice: EXPERIMENT (Randomized Controlled Trial)
Justification:
Study Design:
Participants: 200 high school students across multiple schools
Random Assignment: Randomly divide into:
Blinding (optional but ideal): If possible, control group could use a placebo app (same interface, no learning features) to match the experience
Response Variable: Exam scores on a standardized exam administered at week 9 (after 8 weeks of treatment)
Analysis: Compare average exam scores between groups; if treatment mean >> control mean, the app shows causal benefit
Why not observational? Students self-selecting to use the app differ systematically from non-users in motivation, study habits, etc., making it impossible to isolate the app's effect.