How many continuous variables is the Pearson Correlation Coefficient used with?

The Pearson Correlation Coefficient is designed to measure the strength and direction of the linear relationship between two continuous variables. This statistical tool quantifies how closely the two variables are related to each other, making it important in various analyses that look for correlations.

While you can include additional variables in a broader study, the Pearson Correlation specifically requires only two continuous variables to compute the correlation coefficient. This is foundational in statistics, as its calculation depends solely on pairs of observations from two different continuous variables. As a result, the correct understanding is that it is fundamentally utilized with two or more continuous variables when evaluating relationships, but the direct calculation is strictly between two variables at a time.