A multiple regression model is assessed to be good if the error sum of squares SSE and the standard error of estimate s _{$\varepsilon$} are both small,the coefficient of determination R² is close to 1,and the value of the test statistic F is large.

Question

Quizplus · Accepted Answer

This statement is accurate and reflects commonly accepted criteria for assessing the goodness of fit of a multiple regression model. The SSE and sF1F1F1S1_F1F1F10 values should be small, meaning that the model accurately predicts the outcome variable. The coefficient of determination, R2, should be close to 1, indicating that the predictors explain a large amount of the variance in the outcome variable. Finally, the F-test should produce a large value, indicating that the model is significant and the predictors are jointly related to the outcome variable.

A Multiple Regression Model Is Assessed to Be Good If ε\varepsilonε

A Multiple Regression Model Is Assessed to Be Good If $\varepsilon$