If multicollinearity exists among the independent variables included in a multiple regression model, then:
A)regression coefficients will be difficult to interpret.
B)the standard errors of the regression coefficients for the correlated independent variables will increase.
C)coefficient of determination will assume a value close to zero.
D)the standard errors of the regression coefficients for the correlated independent variables will increase and coefficient of determination will assume a value close to zero.

Question

Quizplus · Accepted Answer

Multicollinearity leads to an increase in the standard errors of the regression coefficients for the correlated independent variables, making it difficult to interpret the regression coefficients. It also results in a decrease in the coefficient of determination, which assumes a value close to zero. Hence, both options B and C are incorrect. The best choice is D, which correctly captures the effects of multicollinearity.

If Multicollinearity Exists Among the Independent Variables Included in a Multiple