Question 2 (25 points) In this exercise you will investigate the relationship between housing prices and the physical characteristics of a home. On Canvas you will find a data file hprice.xls (in Excel format), collected from the real estate pages of the Boston Globe in 1990 (these are homes selling in the Boston, MA area). It contains data on the selling price (price) of the house (in $1000), the size (sqrft) of the house in square feet, the number of bedrooms (bdrms), the size of the lot (lotsize) in square feet, and a dummy variable (colonial) which is equal to 1 if the home was colonial style. Use these data to answer the following questions. In all your regressions, please include an intercept term. Make sure to include your Stata/R output with your homework (a) (4 points) Run a regression of selling price (price) on the size of the home (sqrft) and the number of bedrooms (bdrms) and report your results. (b) (2 points) What is the estimated increase in price for a house with one more bedroom, holding square footage constant? (e) (2 points) What is the estimated increase in price for a house with an additional bedroom that is 140 square feet in size? Compare this to your result in part b). (a) (2 points) What percentage of the variation in price is explained by square footage and the number of bedrooms? Question 2 (25 points) In this exercise you will investigate the relationship between housing prices and the physical characteristics of a home. On Canvas you will find a data file hprice.xls (in Excel format), collected from the real estate pages of the Boston Globe in 1990 (these are homes selling in the Boston, MA area). It contains data on the selling price (price) of the house (in $1000), the size (sqrft) of the house in square feet, the number of bedrooms (bdrms), the size of the lot (lotsize) in square feet, and a dummy variable (colonial) which is equal to 1 if the home was colonial style. Use these data to answer the following questions. In all your regressions, please include an intercept term. Make sure to include your Stata/R output with your homework (a) (4 points) Run a regression of selling price (price) on the size of the home (sqrft) and the number of bedrooms (bdrms) and report your results. (b) (2 points) What is the estimated increase in price for a house with one more bedroom, holding square footage constant? (e) (2 points) What is the estimated increase in price for a house with an additional bedroom that is 140 square feet in size? Compare this to your result in part b). (a) (2 points) What percentage of the variation in price is explained by square footage and the number of bedrooms