Lesson 203 of 1570
Correlation vs. Causation
The most famous warning in statistics is also the most ignored. Here is how to actually tell them apart.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1Two Things Move Together
- 2correlation
- 3causation
- 4confounding
Concept cluster
Terms to connect while reading
Section 1
Two Things Move Together
Correlation means two things go up and down together. Causation means one of them actually causes the other. It is easy to find correlations. It is much harder to establish causation.
Why they get confused
- Ice cream sales and drowning both rise in summer — not because ice cream drowns you
- Users who open the chatbot more convert more — but causation could run either way
- Countries with more storks have higher birth rates — confounded by rural/urban differences
What actually establishes causation
- 1Randomized controlled trial: you intervene (the gold standard)
- 2Natural experiments: accidental random assignment in the wild
- 3Instrumental variables: a variable affecting A but not B directly
- 4Causal inference frameworks (Pearl's do-calculus, potential outcomes)
Compare the options
| Correlational claim | Causal claim |
|---|---|
| Users who use feature X convert more | Launching feature X will increase conversions |
| Models with more parameters score higher | Adding parameters would raise this model's score |
| People who read self-help books are happier | Reading self-help makes people happier |
“Correlation does not imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'.”
Key terms in this lesson
The big idea: correlations are the fuel of science, but not its conclusion. Ask what experiment would distinguish the stories before you believe one.
End-of-lesson quiz
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