# Correlation and causation

Correlation means two variables move together. It does not prove one causes the other. A third factor (a confounder) may drive both, or the link may be chance.

Statistics (university) · Part 08: Correlation and regression · Card 9 of 9 · Last updated 2026-10-19

## Analogy

Ice cream sales and sunburn rise together. Hot weather causes both. Ice cream does not cause sunburn.

## Example

**A hidden driver**

Summer heat raises ice cream sales
Summer heat raises sunburn cases
Sales and sunburn correlate
But neither causes the other

## In practice

Only a randomised experiment, where chance assigns who gets the treatment, can support a cause claim.

## Practice

### Flashcards

- **What is a confounder?** A third variable that influences both the cause and the effect.

### Interview questions

**A study finds that cities with more ice cream shops have more sunburn. Explain why this does not mean ice cream causes sunburn, and how you could find out.**

- Correlation does not prove cause
- A confounder such as hot weather drives both
- Randomised experiments can test cause
- Regression can adjust for measured confounders

## Questions people ask

### How can I tell if a correlation is causal?

Look for a randomised experiment, a plausible mechanism, a consistent result across studies, and a cause that comes before the effect. Rule out confounders. Observational data alone rarely settles causation, however strong the correlation looks, and a fancy model cannot fix a weak design.

### What is a confounding variable?

A confounder is a third variable linked to both the supposed cause and the effect, creating a misleading link. Hot weather confounds ice cream and sunburn. Randomised experiments spread confounders evenly across groups, while regression can adjust for those you measured.

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