Selling Price Total No. of Attached Garage Observation (x $1000) Size (x 100 ft]) Rooms Age (No= 0, Yes= 1) Y X1 X2 X4 265.2 12.0 6 17 0 279.6 20.2 7 18 0 311.2 27.0 7 17 328.0 30.0 8 18 1 352.0 30.0 8 15 1 281.2 21.4 20 288.4 21.6 7 0 8 292.8 25.2 7 9 356.0 37.2 9 10 263.2 14.4 7 11 272.4 15.0 7 17 0 12 291.2 22.4 6 9 0 13 299.6 23.9 7 20 14 307.6 26.6 6 23 15 320.4 30.7 7 23 a. Using a computer regression program, determine the estimated regression equation with the four explanatory variables shown in the tables. b. Give an economic interpretation of each of the estimated regression coefficients c. Which of the independent variables (if any) are 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. Construct an approximate 95 percent prediction interval for the selling price of a 15-year old house having 1,800 square, 7 rooms, and an attached garage