Function

Correlation describes the strength of a linear relationship between two variables.

Regression tells us how to draw the straight line described by the correlation.

Purpose

To determine the degree of relationship between two variables.

To model the relationship between variables and predict the value of a dependent variable based on one or more independent variables.

Focus

The strength and direction (positive, negative, or none) of the linear association.

The effect of one variable on another.

Output

A correlation coefficient (typically between -1 and +1), showing the strength and direction of the relationship.

A regression equation that can be used to make predictions.

Causation

Does not imply causation; it only indicates a relationship.

Can be used to explore or infer cause-and-effect relationships.

Example

Shows a relationship between study time and grades, but doesn't prove that studying causes better grades.

Can be used to predict a student’s final grade based on their study time, potentially suggesting a causal relationship.