i. A coefficient of multiple determination equaling -0.76 is definitely possible. ii. Multiple R²measures the proportion of explained variation relative to total variation. iii. The number of degrees of freedom associated with the regression sum of squares in the regression equation model equals the number of independent variables. A) (i), (ii), and (iii) are all correct statements. B) (i) and (ii) are correct statements but not (iii). C) (i) and (iii) are correct statements but not (ii). D) (ii) and (iii) are correct statements but not (i). E) (i), (ii), and (iii) are all false statements.

Question

Quizplus · Accepted Answer

- The coefficient of multiple determination, often denoted as $R^2$, cannot be negative. It ranges from 0 to 1, where 0 indicates no explanatory power and 1 indicates perfect explanatory power of the independent variables over the dependent variable.- Multiple $R^2$ indeed measures the proportion of the variance in the dependent variable that is predictable from the independent variables, indicating the proportion of explained variation relative to the total variation.- The number of degrees of freedom associated with the regression sum of squares equals the number of independent variables, as it reflects the number of explanatory variables used in the model.

I a Coefficient of Multiple Determination Equaling -0