Multicollinearity refers to correlations among the dependent variables and makes predictions much more accurate because predicting one variable also allows you to predict the correlated variable(s).

Question

Quizplus · Accepted Answer

Multicollinearity actually decreases the accuracy of predictions because it makes it difficult to determine the individual effect of each independent variable on the dependent variable. It also leads to unstable regression coefficients and inflated standard errors.

Multicollinearity Refers to Correlations Among the Dependent Variables and Makes