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Correlation vs. Causation: What's the Difference?

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University Course Reader · STEM

The authors caution that the link is a correlation and that the data cannot establish cause.

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Correlation denotes statistical association between two variables, whereas causation denotes that variation in one produces variation in the other. Association may arise from confounding, reverse causation, selection effects, or chance, and therefore does not establish causality; causal inference requires experimental manipulation or, absent that, converging observational evidence assessed against criteria such as temporality, dose response, and mechanistic plausibility.

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