Computational Approach - Interpreting the Correlation Coefficient R
Customarily, the degree to which two or more predictors (independent or X variables) are related to the dependent (Y) variable is expressed in the correlation coefficient R, which is the square root of R-square. In multiple regression, R can assume values between 0 and 1. To interpret the direction of the relationship between variables, look at the signs (plus or minus) of the regression or B coefficients. If a B coefficient is positive, the relationship of this variable with the dependent variable is positive (e.g., the greater the IQ the better the grade point average); if the B coefficient is negative, the relationship is negative (e.g., the lower the class size the better the average test scores). Of course, if the B coefficient is equal to 0, there is no relationship between the variables.