4. Data were collected from a random sample of 220 home sales from a community in 2013. Let Price denote the selling price (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), 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." The regression model is Price Bo+BBDR+ BBath + B3Hsize + B4Lsize+BsAge - BPoor, and the estimated regression yields Price 119.2+0.485B DR+ 23.4Bath + 0.156 Hsize + 0.002Lsize + 0.090 Age - 48.8Poor, (23.9) (2.61) (8.94) and adjusted R2 = 0.72, SER=41.5. I (0.011) (0.00048) (0.311) (a) Suppose a homeowner converts part of an existing family room in her house into a new bathroom. What is the expected increase in the value of the house? (b) 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? (10.5)