A problem area for marketing researchers in multiple regression is when the independent variables are highly correlated among themselves.

Question

Quizplus · Accepted Answer

When the independent variables in a multiple regression analysis are highly correlated among themselves, it can lead to multicollinearity issues. This means that the predictive power of the model may decrease, and it becomes difficult to interpret the individual effects of the independent variables on the dependent variable. Thus, it is generally advisable for researchers to avoid including highly correlated independent variables in the same regression model.

A Problem Area for Marketing Researchers in Multiple Regression Is