Statistical Methods of Business II – Case Study – Indiana Real Estate
Ann Perkins, a realtor in Brownsburg, Indiana, would like to use estimates from a multiple regression model to help prospective sellers determine a reasonable asking price for their homes. S
he believes that the following four factors influence the asking price (Price) of a house:
1) The square footage of the house (SQFT)
2) The number of bedrooms (Bed)
3) The number of bathrooms (Bath)
4) The lot size (LTSZ) in acres
She randomly collects online listings for 50 single-family homes.
Part 1 – Provide summary statistics (with Excel Data Analysis) by calculating the mean and standard deviation on the asking price, square footage, the number of bedrooms, the number of bathrooms, and the lot size. Explain each factor’s mean and standard deviation. What does
each of these summary statistics tell us.
Part 2 – Estimate and interpret a multiple regression model where the asking price is the response variable and the other four factors are the explanatory variables.
The end result should be a Excel Regression Output
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Adj. R Square
Standard
Error
Observations
ANOVA
Df SS MS F Significance F
Regression
Residual
Total
Coefficients
Standard
Error t Stat P-value Lower 95% Upper 95%
Intercept
SQFT
Bed
Bath
LTSZ
Also provide the estimate model equation: Price =
Part 3 – Interpret the resulting coefficient of determination.
Part 4 – Write your findings in thorough, concise, and well-written report form. For an example review and refer to other reports throughout your textbook. There is at least one at the end of each chapter.
Note you are expected to use proper statistical terminology when appropriate but remember you are writing for a group who may not be as knowledgeable about statistics as you are. You must be sure they can understand your findings while also writing a professional report.
Part 5– Prepare your report in a PowerPoint Presentation and record your presentation. Introduction Title Slide: State your name, institution, the course, your professor’s name, the case study title.
Give a brief description of the background by providing an overview of the case study.
Present the type of statistical method used and why you chose it in order to find a solution.
Respond to the Case Study problem statements by evaluating, analyzing, and interpreting your statistical analysis. Slides should be developed to show how you solved the calculations. Here you would include your Excel data analysis output.
Summarize your findings in a conclusion. What should the real estate agent report to the sellers and why?
