To evaluate the assumption of linearity, a multiple regression analysis should include
A) calculation of variance inflation factors.
B) hypothesis tests of individual regression coefficients.
C) scatter diagrams of the dependent variable plotted as a function of each independent variable.
D) an ANOVA table.

Question

Quizplus · Accepted Answer

Scatter diagrams of the dependent variable plotted as a function of each independent variable is the best choice to evaluate the assumption of linearity. This helps to visually inspect if there is a linear relationship between the dependent variable and each independent variable, allowing identification of potential issues such as curvilinear relationships or outliers. Variance inflation factors, hypothesis tests of individual coefficients, and ANOVA tables are useful for other aspects of multiple regression analysis, but not specifically for evaluating linearity assumptions.

To Evaluate the Assumption of Linearity, a Multiple Regression Analysis