Multiple Regression with Four Independent Variables
and One Dependent Variable
Please wait until the page is fully loaded.
This page will perform a basic multiple regression analysis for the case where there are four independent or predictor variables, X_{1}, X_{2}, X_{3}, and X_{4}, and one dependent or criterion variable, Y. To proceed, double click in the cell labeled "X1X2" and type in the value of r for the correlation between X_{1} and X_{2}. Then double click in the cells labeled "X1X3," "X1X4," and so on, and type in the values of r for the correlations between X_{1} and X_{3}, X_{1} and X_{4}, and so on. The mirrorimage values of r in the cells below the diagonal line of "1.0" entries will be entered automatically. A negative value of r should be preceded by a minus sign: e.g., .76 . Do not enter a plus sign; all entered values are assumed to be positive unless preceded by "".
After all values of r have been entered, click the "Calculate" button. To perform a new analysis with a different set on intercorrelations, click the "Reset" button.
 X_{1}
 X_{2}
 X_{3}
 X_{4}
 Y

X_{1}






X_{2}






X_{3}






X_{4}






Y






 X_{1}
 X_{2}
 X_{3}
 X_{4}

B = Standardized Regression Weight





B x r_{xy}





R^{2} = total proportion of Y variance accounted for
by the combination of X_{1}, X_{2}, X_{3}, and X_{4}.
Close this page to return to the VassarStats main menu.

Home
 Click this link only if you did not arrive here via the VassarStats main page.

©Richard Lowry 19981999
All rights reserved.