Correlation vs. Causation

In probability theory and statistics, correlation, also called correlation coefficient, indicates the strength and direction of a linear relationship between two random variables. In general statistical usage, correlation or co-relation refers to the departure of two variables from independence, although correlation does not imply causation. In this broad sense there are several coefficients, measuring the degree of correlation, adapted to the nature of data.

Correlation does not imply causation is a phrase used in statistics to indicate that correlation between two variables does not imply there is a cause-and-effect relationship between the two. Its negation correlation implies causation is a logical fallacy by which two events that occur together are prematurely claimed to have a cause-and-effect relationship. It is also known as cum hoc ergo propter hoc (Latin for "with this, therefore because of this") and false cause.