Regression Analysis

question d

Interpret the estimates b1 in model (2) and (3). Compare magnitudes across all models.

Regression Analysis . You would like to study the relationship between the sale price of a house and its characteristics. For this purpose you decide to explore data containing sale prices of 546 houses, sold during July, August and September of 1987, in the city of Windsor, Canada, along with their important features. The following characteristics are available: the lot size of the property in square feet, the numbers of bedrooms and bathrooms. In addition there are dummy variables for the presence of central air conditioning, a driveway, and a basement. You estimate the following regres- sion models: log(Price) = Bo + Bi log(Lot Size) + B2X2 + ... +B6X6 +u, where X2, ...,Xo represent the available house characteristics. The results of the estima- tion are presented in the table with standard errors in parentheses: Constant log(Lot Size) # Bedrooms # Bathrooms (1) (2) (3) 6.469 7.094 7.363 (0.277) (0.232) (0.225) 0.542 0.400 0.347 (0.033) (0.028) (0.028) 0.078 0.078 (0.015) (0.015) 0.216 0.209 (0.023) (0.022) 0.212 0.206 (0.024) (0.023) 0.175 (0.030) 0.108 (0.021) 0.336 0.567 0.612 546 546 546 Air Condition Driveway Basement R2 N