A problem in multiple regression when the independent variables are correlated with each other, causing the parameters estimates to be unreliable is called:
A) multi-collinearity
B) interdependence.
C) causality.
D) prediction.

Question

Quizplus · Accepted Answer

Multi-collinearity occurs when two or more independent variables in a multiple regression model are highly correlated with each other. This means that it becomes difficult to distinguish the impact of each independent variable on the dependent variable since their effects are intertwined. As a result, the parameter estimates become unreliable, and the model's predictive ability is affected. Therefore, multi-collinearity is a significant problem in multiple regression.

A Problem in Multiple Regression When the Independent Variables Are