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Use the Following to Answer Questions

Question 31

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Use the following to answer questions :
A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the two towns they are considering. The variables they collected are the selling price of the home (in thousands of dollars), the size of the home (in square feet), the age of the home (in years), and the town in which the house is located (coded 1 = Canton and 0 = Potsdam). Output from their multiple regression analysis is provided.
The regression equation is
Price (in thousands) = 69.2 + 0.0627 Size (sq. ft.) - 0.632 Age + 1.6 Town
Use the following to answer questions : A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the two towns they are considering. The variables they collected are the selling price of the home (in thousands of dollars), the size of the home (in square feet), the age of the home (in years), and the town in which the house is located (coded 1 = Canton and 0 = Potsdam). Output from their multiple regression analysis is provided. The regression equation is Price (in thousands) = 69.2 + 0.0627 Size (sq. ft.) - 0.632 Age + 1.6 Town     S = 40.0763 R-Sq = 59.3% R-Sq(adj) = 56.5% Analysis of Variance    -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
S = 40.0763 R-Sq = 59.3% R-Sq(adj) = 56.5%
Analysis of Variance
Use the following to answer questions : A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the two towns they are considering. The variables they collected are the selling price of the home (in thousands of dollars), the size of the home (in square feet), the age of the home (in years), and the town in which the house is located (coded 1 = Canton and 0 = Potsdam). Output from their multiple regression analysis is provided. The regression equation is Price (in thousands) = 69.2 + 0.0627 Size (sq. ft.) - 0.632 Age + 1.6 Town     S = 40.0763 R-Sq = 59.3% R-Sq(adj) = 56.5% Analysis of Variance    -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 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
Use the following to answer questions : A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the two towns they are considering. The variables they collected are the selling price of the home (in thousands of dollars), the size of the home (in square feet), the age of the home (in years), and the town in which the house is located (coded 1 = Canton and 0 = Potsdam). Output from their multiple regression analysis is provided. The regression equation is Price (in thousands) = 69.2 + 0.0627 Size (sq. ft.) - 0.632 Age + 1.6 Town     S = 40.0763 R-Sq = 59.3% R-Sq(adj) = 56.5% Analysis of Variance    -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
S = 39.6368 R-Sq = 59.3% R-Sq(adj) = 57.5%
Analysis of Variance
Use the following to answer questions : A quantitatively savvy, young couple is interested in purchasing a home in northern New York. They collected data on houses that had recently sold in the two towns they are considering. The variables they collected are the selling price of the home (in thousands of dollars), the size of the home (in square feet), the age of the home (in years), and the town in which the house is located (coded 1 = Canton and 0 = Potsdam). Output from their multiple regression analysis is provided. The regression equation is Price (in thousands) = 69.2 + 0.0627 Size (sq. ft.) - 0.632 Age + 1.6 Town     S = 40.0763 R-Sq = 59.3% R-Sq(adj) = 56.5% Analysis of Variance    -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

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Yes, the model without Town (i.e., using...

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