Multicollinearity is desirable in multiple regression.

Name: Multicollinearity is desirable in multiple regression.
Brand: Quizplus
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Quizplus · Accepted Answer

Multicollinearity refers to a situation in which two or more explanatory variables in a multiple regression model are highly linearly related, making it difficult to isolate the individual effects of the variables on the dependent variable. This is generally undesirable as it increases the variance of the coefficient estimates and makes the model interpretation more challenging.

Multicollinearity Is Desirable in Multiple Regression