Coefficient of multiple determination

The coefficient of multiple determination (or R2) is a measure of how much of the variation in a dependent variable is explained by all the independent variables in a regression model. It's calculated by taking the square of the correlation coefficient—the proportion of the variation in the dependent variable that is explained by each independent variable—and multiplying this by the number of independent variables. A higher R2 indicates that more of the variation in the dependent variable is explained by the model, while lower R2 indicates that less of the variation is explained by the model.