In multiple regression analysis, the multiple correlation coefficient (R)
A) is the value by which the score on an independent variable is multiplied to predict the score on the dependent variable.
B) represents the degree of association between the independent variables as a set and the dependent variable.
C) represents the increase in the proportion of variance in the dependent variable that is accounted for by adding another independent variable to the regression equation.
D) represents the condition that arises when two or more predictor variables are highly correlated with each other.

Question

Quizplus · Accepted Answer

The multiple correlation coefficient (R) represents the degree of association between the independent variables as a set and the dependent variable. It ranges from -1 to +1, with higher values indicating stronger relationships between the variables. It does not have anything to do with multiplying scores or the proportion of variance accounted for by adding another independent variable, and it is not affected by multicollinearity between independent variables.

In Multiple Regression Analysis, the Multiple Correlation Coefficient (R)