Two simple regression models were used to predict a single dependent variable.Both models were highly significant,but when 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

The statement suggests that adding a second independent variable to the multiple regression model did not substantially increase the coefficient of determination (R²) and the parameter estimates were not significantly different from 0. This indicates that the two independent variables are highly correlated, leading to issues of collinearity in the model.

Two Simple Regression Models Were Used to Predict a Single