MBA 6300 Case Study No. 2

There are numerous variables that are believed to be predictorsof housing prices, including living area (square feet), number ofbedrooms, and number of bathrooms. The data in the CaseStudy No. 2.xlsx file pertains to a random sample ofhouses located in a particular geographic area.

1. Develop the following simple linear regression models topredict the sale price of a house based upon a 90% level ofconfidence. Write the regression equation for each model.
   1. Sale price based upon square feet of living area.
   2. Sale price based upon number of bedrooms.
   3. Sale price based upon number of bathrooms.
2. Develop the following multiple linear regression models topredict the sale price of a house based upon a 90% level ofconfidence. Write the regression equation for each model.
   1. Sale price based upon square feet of living area and number ofbedrooms.
   2. Sale price based upon square feet of living area and number ofbathrooms.
   3. Sale price based upon number of bedrooms and number ofbathrooms.
   4. Sale price based upon square feet of living area, number ofbedrooms, and number of bathrooms.
3. Discuss the joint statistical significance of each of thepreceding simple and multiple linear regression models at a 90%level of confidence and 95% level of confidence.
4. Discuss the individual statistical significance of thecoefficient for each independent variable for each of the precedingsimple and multiple linear regression models at a 90% level ofconfidence and 95% level of confidence.
5. Compare any of the preceding simple and multiple linearregression models that were found to be jointly and individuallystatistically significant at a 90% level of confidence and selectthe preferred regression model. Explain your selection using theappropriate regression statistics.
6. Interpret the coefficient for each independent variable (orvariables) associated with your selected preferred regressionmodel.
7. Using the preferred regression model, predict the sale price ofa house with the following values for the independent variables:3,000 square feet of living area, 3 bedrooms, and 2.5 bathrooms.(Hint: You should only use the values for those independentvariables that are specifically associated with your selectedpreferred regression model.)

Prepare a single Microsoft Excel file using a separateworksheet for each question and upload your Excelfile.

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