Which of the following statements about multicollinearity in multiple regression analysis is FALSE?
A) Multicollinearity exists when two or more independent variables in a multiple regression analysis are highly correlated with one another.
B) Multicollinearity causes problems for the interpretation of the results of a multiple regression analysis.
C) Multicollinearity might be a problem when a study uses multiple operational definitions of an independent variable.
D) Multicollinearity improves the ability of a multiple regression analysis to predict scores on a dependent variable.

Question

Quizplus · Accepted Answer

This statement is false. Multicollinearity actually undermines the predictive ability of a multiple regression analysis by making it difficult to determine the specific contributions of each independent variable to the prediction of the dependent variable. Therefore, options A, B, and C are true statements.

Which of the Following Statements About Multicollinearity in Multiple Regression