What is the difference between correlation and causation? How would you test if a change causes an outcome?
What the interviewer wants to hear
- Correlation is association; causation means changing X changes Y
- Confounders, reverse causation and chance create correlation
- Randomised experiments are the best test
- Observational methods when experiments are not possible
Model answer
Correlation means two things move together. Causation means changing one actually changes the other. Correlation can appear without causation because of a confounder, a third factor that drives both, like hot weather increasing both ice cream sales and drownings. It can also come from reverse causation, where Y actually causes X, or just from chance when we look at many variables. The cleanest way to test causation is a randomised experiment, like an A/B test: randomly give the change to some users, and because the groups are similar in every other way, the difference in outcome is caused by the change. When I cannot run an experiment, I use methods like difference-in-differences or matching, and I am honest that conclusions are weaker and depend on assumptions.
Can you answer it under time pressure?
Take a timed easy round and get scored on every answer.
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