The county assessor feels that the use of more independent variables in the regression equation might improve the overall explanatory power of the model. In addition to size, the assessor feels that the total number of rooms, age, and whether or not the house has an attached garage might be important variables affecting selling price. The data for the 15 randomly selected dwellings are shown in the following table.
a. Using a computer regression program, determine the estimated regression equation with the four explanatory variables shown in the following table.
b. Give an economic interpretation of each of the estimated regression coefficients.
c. Which of the independent variables (if any) is statistically significant (at the .05 level) in explaining selling price?
d. What proportion of the total variation in selling price is explained by the regression model?
e. Perform an F-test (at the 5 percent significance level) of the overall explanatory power of the model.
f. Construct an approximate 95 percent prediction interval for the selling price of a 15-year-old house having 1,800 square feet, 7 rooms, and an attachedgarage.

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