The distance between the Y value in the data and the Y value predicted from the regression equation is known as the residual.What is the value for the sum of the squared residuals? A)SS_residual = r²(SS_X) B)SS_residual = (1 - r²)(SS_X) C)SS_residual = r²(SS_Y) D)SS_residual = (1 - r²)(SS_Y)

Question

Quizplus · Accepted Answer

The sum of the squared residuals is given by the formula $SS_{residual} = (1 - r^2)(SS_Y)$, where $r^2$ is the coefficient of determination and $SS_Y$ is the total sum of squares for the dependent variable. This formula reflects the proportion of the variance in the dependent variable that is not explained by the model.

The Distance Between the Y Value in the Data and the Y