Consider the following regression:
Price = 118.3 + 0.548BDR + 24.6Bath + 0.112Hsize + 0.005Lsize + 0.051Age - 47.5Poor, RĀ² = 0.73, SER = 41.5
(23.7) (2.34) (8.97) (0.013) (0.00047) (0.349) (10.4)
where BDR is the # of bedrooms, Bath is the # of bathrooms, Hsize represents the square footage of the house, Lsize the square footage of the lot, Age the age of the house, and Poor is a binary variable that equals to 1 if the house is in a poor condition and 0 otherwise.
16. In the regression above suppose you wanted to test the hypothesis that BDR equals zero. What is the estimated test statistic?
A. 0.25
B. 0.26
C. 0.23
D. 0.19
17. In the regression above, is the # of bedrooms a significant predictor?
A. Yes because it is significant at all levels
B. No because it is not significant at either level
C. Yes because we should always account for # of bedrooms when computing house prices
D. Yes because BDR is highly correlated with Hsize
