Correlation vs. causation refers to the distinction between a statistical relationship where two variables change together (correlation) and a situation where one variable directly affects another (causation). Understanding this difference is crucial when interpreting data and results, as correlation does not imply that one event causes the other, which can lead to misleading conclusions if not properly analyzed.
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