solve

Suppose you have a data set that includes the sale price of homes (price), the area of the home in square feet (area), the number of bedrooms, the lot size in square feet, and the distance in miles from the city center (miles). Model C log(price) = 8p + GB, area + 6.bedrooms + B3log(lot) + B4miles + Model D price = y + Barea + Bybedrooms + f3lot + Bymiles + 6; miles\" + When would model D be preferable to model C? If the miles are in different units than sale price. If the relationship between miles and price displays a non-linear "curved" pattern. If the relationship between miles and price is better interpreted in percentages than levels. If there does not not appear to be a significant relationship between sales price and miles