What distinguishes correlation from causation?

The distinction between correlation and causation lies in the nature of the relationship they describe. Correlation reflects a connection between two variables, indicating that they vary together in a consistent manner, but it does not imply that one variable directly influences the other. This means that two variables can be correlated without one causing the other, possibly due to a third variable or merely by chance.

For instance, an example of correlation can be seen between ice cream sales and the number of people visiting the beach; both increase during warm weather, but one does not cause the other. This highlights the essential aspect of correlation—while it indicates a relationship, it does not imply a direct causal link between the two.

Causation, on the other hand, clearly asserts that changes in one variable directly lead to changes in another, which is a more specific and stronger assertion than correlation. Understanding this distinction is crucial in research, as confusing the two can lead to incorrect conclusions and ineffective interventions.