Case Study Real Estate

Case Study : Real Estate

A real estate agent is trying to understand the pricing of homes in her area, a region comprised of small to midsize towns and a small city. For each of 1200 homes recently sold in the region, the file Real Estate Data holds the following variables:

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  • Sale Price (in$)
  • Lot size (size of the lot in acres)
  • Waterfront (Yes, No)
  • Age (in years)
  • Central Air (Yes, No)
  • Fuel Type (Wood, Oil, Gas, Electric, Propane, Solar, Other)
  • Condition (1 to 5, 1 = Poor, 5 = Excellent)
  • Living Area (living area in square feet)
  • Pct College (% in zip code who attend a four-year colleges)
  • Full Bath (number of full bathrooms)
  • Half Bath (number of half bathrooms)
  • Bedrooms (number of bedrooms)
  • Fireplaces (number of fireplaces)

 

The agent has a family interested in a four bedroom house. Using confidence intervals, how should she advise the family on what the average price of a four bedroom house might be in this area? Compare that to a confidence interval for two bedroom homes. How does the presence of a central air conditioning affect the mean price of houses in this area? Use confidence intervals and graphics to help answer that question.

Explore other questions that might be useful for the real estate agent in knowing how different categorical factors affect the sale price and write up a short report on your findings.

 

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