Answer Happy

A real estate firm wanted to develop a regression equation to estimate the value of a home. The value of the house Y was estimated using data for four explanatory variables: the number of rooms, the size of the lot, the number of bathrooms, and a dummy variable which equals 1 if the house has a garage and if it does not. The results are shown below (12 pts.) ANOVA Degrees or Sum of Sques Mean Square F value freedom Error Regression 204.342.6% 51,060.72 6.20.0013 ETO 205.390.00 8.235.60 Total 29 410.132.88 25 Coefficients mort-stop-value Intercept15.232.50 2.462.50 L 0,08 1941 Rooms 2,178.40 778 2.8 0.00971 Lot 78 22 35450.001575 Baths 2.67520 2.229.30 1.2000.341388 Garage 1,15780463.1 2.5000.019343 A What is the p-value for the overall equation? (pt.) We can conclude that the equation (1 pt.) is significant/is a good predictor of home value is not significant/is not a good predictor of home value Write out the regression equation (2 pts.) B. C. From the equation, what is the estimated value of a house with 9 rooms, a lot size of 7500, 2 bathrooms, and a garage? (show your work at least how you set up this problem) (2 pts.) is not is not D. Please check the appropriate blank (4 pts.) Rooms is significant significant Lot is significant significant Baths is significant significant Garage is significant significant is not is not E. Each additional room increases the value of a house by A garage increases the value of a house by (2 pts. a