Statistics
Observational vs Experimental Studies
Lesson
Studies come in two big flavors. The difference matters because only one of them supports a causal conclusion.
Observational study
The researcher measures but does not intervene. People do what they would normally do; you just record what happens.
Examples: survey, census, tracking, looking at existing records.
Experiment
The researcher imposes a treatment — usually assigning subjects to different conditions (ideally at random) — and measures the response.
Examples: clinical trials, lab tests, A/B testing.
Why it matters
Only experiments can establish CAUSE. Observational studies show correlation but always carry the risk of lurking variables. People who exercise might also eat better; you can’t pin a health outcome on just one.
Spot the type
- “Researchers measured / surveyed / tracked” → observational.
- “Researchers assigned / gave / imposed” → experimental.
How to type your answer
Type 1 for and 2 for .
Practice
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Warm-Up
Quick problems to get going.
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Practice
Standard problems matching the lesson.
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Challenge
Harder problems — edge cases, trickier numbers, multiple steps.
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