Two simple regression models were used to predict a single dependent variable.Both models were highly significant,but when the two independent variables were placed in the same multiple regression model for the dependent variable,R² did not increase substantially and the parameter estimates for the model were not significantly different from 0.This is probably an example of collinearity.

Question

Quizplus · Accepted Answer

When two independent variables are highly correlated, it leads to collinearity which can be identified when parameter estimates are not significantly different from 0 in a multiple regression model.

Two Simple Regression Models Were Used to Predict a Single