The Real Estate Price Case

Introduction

The objective of this paper is to perform a meaningful multiple regression analysis in order to predict the price of real estate property in the Baton Rouge area during the mid 2005, from a list of possible predictors which are considered to be reasonable factors that help explaining the variation in the price of real estate.

The variables considered in the analysis are:

• PRICE = sale price in dollars
• SQFT = total square feet
• BEDROOMS = number of bedrooms
• BATHS = number of bathrooms
• AGE = age in years
• OWNER = 1 if owner occupied; = 2 if vacant; = 3 if tenant
• POOL = 1 if pool present
• TRADITIONAL = 1 if traditional build style; = 2 if townhouse; = 3 if ranch; = 4 if new; = 5 if mobile home; = 6 if garden; = 7 if French; = 8 if cottage; = 9 if contemporary; = 10 if colonial; = 11 if Acadian
• FIREPLACE = 1 if fireplace is present
• WATERFRONT = 1 if on waterfront
• DOM = number of days on the market

The above variables can be used directly in the model, except for two of them that need recoding: TRADITIONAL and OWNER. For Traditional , 10 dummy variables will be defined to correspond to the categories, and Arcadian will be used as the baseline. For Owner , two dummy variables will be used, Owner and Vacant, and tenant will be used as the baseline.

The following model will be attempted initially:

Price: $40.72

Solution: The downloadable solution consists of 25 pages, 1572 words and 16 charts.
Deliverable: Word Document