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Correlation and Causation
“When ice-cream sales rise, drownings also increase. What might cause both?”
01 / SUMMARY
In short
An association may arise through direct causation, reverse causation, a common cause, selection, or chance. Causal inference requires designs and assumptions capable of ruling out rival explanations; correlation alone offers no automatic test.
02 / SEQUENCE
What happens
- 01
You observe two variables changing together.
- 02
You list possible causal directions, common causes, and selection effects.
- 03
You seek a design or additional evidence that can distinguish them.
03 / SCENE
In the wild
Hot weather may raise both ice-cream consumption and time spent swimming. Temperature is a plausible common cause.
04 / LIMIT
The limit
“Correlation does not imply causation” does not mean correlations are useless or only randomized experiments provide causal evidence.
FINAL NOTE
What remains
When you see an association, ask: what earlier variable might move both, and how were the observations selected?
CHECK / 01
Put it to work
How firm is your read?