Correlation describes a statistical relationship between two variables. When one variable changes, the other tends to change in a related way. The relationship can be positive—both rise or fall together—or negative—one rises as the other falls.

A positive correlation appears when taller people tend to weigh more, or when study time and exam scores move in the same direction. A negative correlation appears when hours of television and grades move in opposite directions. The strength of the relationship is measured by how tightly the data points cluster around a line; scatterplots make the pattern visible at a glance.

Correlation does not imply causation. A third variable may drive both, or the direction of influence may run opposite to the expected path. Ice-cream sales and drowning deaths rise together in summer, yet neither causes the other. Researchers therefore treat correlation as a starting point for further investigation rather than a final explanation.

In psychology, correlational studies are common when experimental manipulation is impossible or unethical. They map the landscape of relationships that experiments can later test more rigorously.