Why is multicollinearity a potential problem in a multiple linear regression?
A)It becomes difficult to assess the individual importance of predictors and it decreases the standard errors of the b coefficients making them redundant.
B)It becomes difficult to assess the individual importance of predictors and it increases the standard errors of the b coefficients making them unreliable.
C)It becomes difficult to assess the collective power of predictors as it increases the levels of error in the model.
D)It becomes too easy to assess the individual importance of predictors, making the b coefficients unreliable.

Question

Quizplus · Accepted Answer

Multicollinearity causes the standard errors of the b coefficients to increase, making them unreliable. It becomes difficult to assess the individual importance of predictors because the coefficients become unstable and can change substantially when new variables are added or removed. However, it does not make the coefficients redundant nor increase the levels of error in the model.

Why Is Multicollinearity a Potential Problem in a Multiple Linear