Correlation Doesn’t Mean Causation! But What Does It Mean?

While correlation doesn't imply causation, it is a precise mathematical measurement of how two variables move together in a consistent way relative to their averages. The concept is explained using the Pearson correlation coefficient, which normalizes covariance to a scale of -1 to 1, indicating the strength and direction of a linear relationship. Key limitations are that correlation only captures straight-line patterns, failing to detect strong non-linear relationships, and can be influenced by hidden confounding variables. Therefore, correlation should be viewed not as a definitive explanation but as a useful initial signal that prompts deeper investigation into why a pattern exists.