When two or more independent variables in the same regression model can predict each other better than the dependent variable, the condition is referred to as .
A) autocorrelation
B) heteroscedasticity
C) multicollinearity
D) homoscedasticity

Question

Quizplus · Accepted Answer

Multicollinearity occurs when two or more independent variables in the same regression model are highly correlated with each other. This can cause problems in the model because it becomes difficult to accurately estimate the effect of each independent variable on the dependent variable. In extreme cases, multicollinearity can even lead to coefficients with the wrong signs or standard errors that are inflated.

When Two or More Independent Variables in the Same Regression