Projected sales price of houses
Background
Imagine that you are a data analytics consultant for a firm who wants to get projected sale price of houses from house sale advertisements currently in the market, ignoring their asking price. The housing data (housing.csv)collected by the firm includes 500 sales in the last six months and include the variables. The last column is the outcome variable.
elevation: Elevation of the base of the house
dist_am1: Distance to Amenity 1
dist_am2: Distance to Amenity 2
dist_am3: Distance to Amenity 3
bath: Number of bathrooms
sqft: Square footage of the house
parking: Parking type
precip: Amount of precipitation
price: Final House Sale Price
Now our target was to develop the best possible linear regression model to predict the house sale price using the variables. Interpret the variables included and provide explanation for our choice of best model.