The data in Figure 9.19 are from running a multiple regression analysis to develop a model that

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The data in Figure 9.19 are from running a multiple regression analysis to develop a model that predicts the selling price of homes based on the number of bedrooms, the number of bathrooms, square footage, the age of the home, lot size, the number of garages, and the number of stories.

a. Is the overall model useful in predicting the sale price of homes?

b. Write the population regression equation.

c. Write the estimated regression equation.

d. Find and interpret the coefficient of determination.

e. Using the results from the regression analysis, determine if newer homes have higher selling prices and if larger homes have higher selling prices.

f. Do you think that multicollinearity is a concern?

g. A printout of a best subsets regression is given in Figure 9.20. Find a bestfitting model using the three-model selection criteria of \(R^{2}, R_{\mathrm{adj}}^{2}\), and \(C_{p}\) and justify why you selected this model.

Figure 9.19

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Figure 9.20

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