Business Studies

Apply: Regression Modeling

 

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Purpose 

This assignment provides an opportunity to develop, evaluate, and apply bivariate and multivariate linear regression models.

 

Resources: EXCEL

 

Instructions:

The Excel file for this assignment contains a database with information about the tax assessment value assigned to medical office buildings in a city. The following is a list of the variables in the database:

  • Floor Area: square feet of floor space
  • Offices: number of offices in the building
  • Entrances: number of customer entrances
  • Age: age of the building (years)
  • Assessed Value: tax assessment value (thousands of dollars)

 

Use the data to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics.

 

  • Construct a scatter plot in Excel with Floor Area as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables?
  • Use Excel’s Analysis Tool Pak to conduct a regression analysis of Floor Area and Assessment Value. Is Floor Area a significant predictor of Assessment Value?
  • Construct a scatter plot in Excel with Age as the independent variable and Assessment Value as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables?
  • Use Excel’s Analysis Tool Pak to conduct a regression analysis of Age and Assessment Value. Is Age a significant predictor of Assessment Value?

 

Construct a multiple regression model.

  • Use Excel’s Analysis Tool Pak to conduct a regression analysis with Assessment Value as the dependent variable and Floor Area, Offices, Entrances, and Age as independent variables. What is the overall fit r^2? What is the adjusted r^2?
  • Which predictors are considered significant if we work with α=0.05? Which predictors can be eliminated?
  • What is the final model if we only use Floor Area and Offices as predictors?
  • Suppose our final model is:
  • Assessed Value = 115.9 + 0.26 x Floor Area + 78.34 x Offices
  • What would be the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago? Is this assessed value consistent with what appears in the database?

 

Submit your assignment.

 

ANSWER

 

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