How does correlation differ from causation?

Correlation shows a statistical relationship without direct influence, meaning that two variables may change together but that change does not necessarily mean that one variable is causing the change in the other. Correlation can demonstrate how variables may be associated with each other, such as when two datasets show a similar trend over time, but it does not provide evidence that one variable influences or affects the other.

For instance, a high correlation between ice cream sales and drowning incidents does not imply that buying ice cream causes drowning. Instead, both may be influenced by a third factor, such as warm weather. Thus, understanding this distinction is crucial in data analysis as it helps analysts avoid drawing incorrect conclusions from data relationships.