Data were collected from a random sample of 230 home sales from a community in 2003. Let Price denote the selling price (in $1,000), BDR denote the number of bedrooms, Bath denote the number of bathrooms, Hsize denote the size of the house (in square feet), Size 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 ModifyingAbove Price with caret equals 118.0 plus 0.480 BDR plus 23.2 Bath plus 0.154 Hsize plus 0.002 L'Size plus 0.089 Age minus 48.3 Poor comma Upper R overbar squared equals 0.71 comma SER equals 41.1. Suppose that 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?

Base on the scenario been described in the question, we were told that suppose that a homeowner converts part of an existing family room in her house into a new bathroom. What is the regression’s prediction for the increase in the value of the house? As we can see, the number of bathrooms has increase by one. Therefore, the prediction for the increase in Pis 23.4. As we know Pis is been measured in thousands of $, then we convert to thousand by multiplying 23.4 by 1000 which we have as $23,400. the prediction for the increase in the value of the house is $23,400. As our answer