Regression output for a model that omits Town as a predictor is provided. Assuming that the residuals for this reduced model do not indicate any problems with using multiple regression, is this model an improvement over the model that uses Size, Age, and Town as predictors? Statistically justify your answer by discussing at least two quantitative criteria.
The regression equation is
Price (in thousands) = 70.6 + 0.0624 Size (sq. ft.) - 0.635 Age

S = 39.6368 R-Sq = 59.3% R-Sq(adj) = 57.5%
Analysis of Variance

Question

Regression output for a model that omits Town as a predictor is provided. Assuming that the residuals for this reduced model do not indicate any problems with using multiple regression, is this model an improvement over the model that uses Size, Age, and Town as predictors? Statistically justify your answer by discussing at least two quantitative criteria.
The regression equation is
Price (in thousands) = 70.6 + 0.0624 Size (sq. ft.) - 0.635 Age
  
S = 39.6368 R-Sq = 59.3% R-Sq(adj) = 57.5%
Analysis of Variance

Quizplus · Accepted Answer

The Answer of Regression output for a model that omits Town as a predictor is provided. Assuming that the residuals for this reduced model do not indicate any problems with using multiple regression, is this model an improvement over the model that uses Size, Age, and Town as predictors? Statistically justify your answer by discussing at least two quantitative criteria.
The regression equation is
Price (in thousands) = 70.6 + 0.0624 Size (sq. ft.) - 0.635 Age
  
S = 39.6368 R-Sq = 59.3% R-Sq(adj) = 57.5%
Analysis of Variance

Regression Output for a Model That Omits Town as a Predictor