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 refers to a situation in regression analysis where two or more independent variables in the model are highly correlated with each other, making it difficult to isolate the individual effects of each variable on the dependent variable.

When Two or More Independent Variables in the Same Regression