In regression, multicollinearity is considered problematic when two or more explanatory variables are ________.
A) not correlated
B) rarely correlated
C) highly correlated
D) moderately correlated

Question

Quizplus · Accepted Answer

Multicollinearity is considered problematic when the explanatory variables are highly correlated with each other. This makes it difficult for the regression model to distinguish between the effects of the individual variables and can lead to unreliable coefficient estimates. Therefore, when interpreting the results of a regression analysis, it is important to check for multicollinearity among the explanatory variables.

In Regression, Multicollinearity Is Considered Problematic When Two or More