List Price Price of house in dollars r Number of rooms br Number of bedrooms b Number of Bathrooms a Age (years) style 1 if bungalow, 2 if two storey S Living area (Square Metres) g Number of Garage Space att 1 if attached, 0 if detached bas Basement (from 1 (open) to 3 (finished) f Number of fireplaces (woodburning) lots Lot Size (square metres) e Exposure of Yard (N, NE, E= 1, 0 otherwise) Your task is to formulate and estimate a linear regression model with house price as the dependent variable. Specifically, you are asked to: Write out at least 3 equations you initially wish to estimate and justify the inclusion of the chosen variables. Include your a priori expectations for the sign of each coefficient. Don't take the attitude that you should include every possible variable and functional form modification and then drop the insignificant ones. Use theory and intuition to try and find the best model you can first time around. Comment on the theory behind the choices you made (e.g. functional form) b. Create a dummy variable indicating whether the house has a garage or not (where 0=no garage and 1=has a garage). (Note: You may create other dummies indicating, e.g., whether the house has a fireplace; whether the house has a finished basement; etc...) c. Describe your data using descriptive statistics for continuous (or quantitative) variables (e.g. mean, standard deviation, minimum and