Question: The following results are from data where the dependent variable is the selling price of used cars, the independent variables are MSRP_Amt (which is what the car sold for when it was new), Leather (which is a dummy variable = 1 if the car has leather and = 0 otherwise), Manual (which is a dummy variable = 1 if the car has a manual transmission and = 0 otherwise), Mileage_Sale (which is the mileage on the car), Age (how old the car is in months), and RepairAmt (which is the estimated amount of repair work that exists on the car).

a) Complete the results: (20)

Based on the regression results:

b) What is the estimated regression equation? (5)

c) How much of the variation in selling price is explained by the regressors? (5)

d) What is the standard error of the error term in the regression equation? (5)

e) Are any of the explanatory (independent) variables significant at the 10% level of significance? How do you know? (5)

f) What is the null and alternative hypothesis that Excel is testing in reporting the t-stats above? (5)

g) Is the regression equation as a whole significant at the 1% level of significance? How do you know? (5)

h) What is the effect on selling price of a car WITH LEATHER versus WITHOUT LEATHER? (5)

i) The used-car dealership only wants to make needed repairs to the car if they are very sure that spending money to repair damages increases the selling price of the car by at least as much as the cost to repair the damages, ie, they want to test whether the coefficient of RepairAmt is at least 1.00. Test the hypothesis that this coefficient is at least 1.00 (at the 5% level of significance). (15)

j) What is the predicted price of a car if MSRP = 24,000, Mileage_Sale = 20.4, Age = 36, RepairAmt = 600 and the car has Leather and a Manual transmission? (10)

k) What is the predicted price of a car if MSRP = 28,000, Mileage_Sale = 16.4, Age = 24, RepairAmt = 1200 and the car has Leather and does not have a Manual transmission? (10)