Simple linear regression analysis differs from multiple regression analysis in that:
A)Simple linear regression uses only one explanatory variable.
B)The coefficient of correlation is meaningless in simple linear regression.
C)Goodness-of-fit measures cannot be calculated with simple linear regression.
D)The coefficient of determination is always higher in simple linear regression.

Question

Quizplus · Accepted Answer

Simple linear regression uses only one explanatory variable, whereas multiple regression analysis uses two or more. The coefficient of correlation and goodness-of-fit measures are still meaningful in simple linear regression, but the coefficient of determination may be higher or lower depending on the specific data and model.

Simple Linear Regression Analysis Differs from Multiple Regression Analysis in That