In [[statistics]], the coefficient of '''multiple correlation''' is a measure of how well a given variable can be predicted using a linear function of a set of other variables. It is measured by the [[coefficient of determination]], but under the particular assumptionassumptions that an intercept is included and that the best possible linear predictors are used, whereas the coefficient of determination is defined for more general cases, including those of nonlinear prediction and those in which the predicted values have not been derived from a model-fitting procedure. The coefficient of multiple determination takes values between zero and one; a higher value indicates a better predictability of the [[dependent and independent variables|dependent variable]] from the [[dependent and independent variables|independent variables]], with a value of one indicating that the predictions are exactexactly correct and a value of zero indicating that no linear combination of dependent variables is better than the simpler predictor which consists of mean of the target variable.
