A business analyst at a major real estate firm wants to build a regression model that will predict the price of a single- family home based on a number of explanatory variables. The real estate firm’s data base has an enormous amount of information on selling prices of homes and potential variables that are related to that price. After a number of discussions with experienced realtors, you decide to model price of a home as a function of the following variables: size of home in terms of floor space, lot size, number of bathrooms, number of bedrooms, age of home, garage size, number of months home has been on the market, distance to nearest elementary school, type of neighborhood, traffic volume on street, and racial mixture of neighborhood.
a. Would you expect any of these variables to be highly correlated?
b. How would you determine if there was a high correlation?
c. What impact would a high correlation between independent variables have on the fitted regression?