6.5 Data were collected from a random sample of 200 home sales from a community in 2013. Let Price denote the selling price (in $1000), 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), Age denote the age of the house (in years), and Poor denote a binary variable that is equal to 1 if the condition of the house is reported as “poor.” An estimated regression yields

a. Suppose a homeowner converts part of an existing family room in their house into a new bathroom. What is the expected increase in the value of the house?

b. Suppose that a homeowner adds a new bathroom to their house, which increases the size of the house by 80 square feet. What is the expected increase in the value of the house?

c. What is the loss in value if a homeowner lets their house run down, such that its condition becomes “poor?”

d. Compute the R2 for the regression.

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Price = 109.7 0.567BDR + 26.9Bath + 0.239Hsize +0.005Lsize +0.1Age 56.9Poor, R2 = 0.85, SER = 45.8. -