Consider the following estimated regression for 220 home sales from a community in 2019 (estimated standard errors in parentheses) Price = 119.2 + 0.485BDR + 23.4Bath + 0.156Hsize + 0.002Lsize +...

Extracted text: Consider the following estimated regression for 220 home sales from a community in 2019 (estimated standard errors in parentheses) Price = 119.2 + 0.485BDR + 23.4Bath + 0.156Hsize + 0.002Lsize + 0.09Age (8.94) (2.61) (0.011) (0.00048) (0.311) R2 = 0.72 where Price denote the selling house price (measured in $1000s), BDR denote the number of bedrooms, Bath denote the number of bathrooms, Hsize denote the size of the house (in square feet), Lsize denote the lot size (in square feet), and Age denote the age of the house (in years). (a) Suppose a homeowner adds a new bathroom to her house, which increases the size of the house by 100 square feet. What is the expected increase in the value of the house (b) Is the coefficient corresponding to BDR statistically different from zero? (c) Typically, five-bedroom houses sell for much more than two-bedroom houses. Is this consistent with your answer to (a) and with the regression more generally? (d) Lot size is measured in square feet. Do you think that another scale might be more appropriate? Why or why not? (e) The F-statistic for omitting BDR and Age from the regression is F = 0.08. Are the coefficients on BDR and Age statistically different from 0 at a 10% significance level?