Lesson 10: Applied Regression Modeling (2 of 2)

September 24, 2020

Review:

Presentation:

  • Dummy Variables
    • incorporate categorical variables
    • binary – value is either 1 or 0
    • if 0, then the coefficient has no effect on y-hat
    • if 1, then the coefficient is added to (or subtracted from) the estimate
  • Demonstration with Sample Real Estate data
    • create a dummy variable for a neighborhood

Assignment:

  • Multiple Regression Analysis
    • Select the worksheet corresponding to the last digit of your PID from this file: PuebloRealEstate_Exam2Data_ByPID
    • Save a copy of the data and convert to .xlsx format
    • Use Excel with the Analysis Toolpak Add-in
    • Build a regression model to estimate selling price
      • You must use 1 interaction variable
      • You must use 1 or more Dummy variables to incorporate neighborhoods
      • Experiment with multiple combinations of variables to find the best model, maximizing R^2 and the F Statistic
    • Add this model to the Lesson 9 spreadsheet
    • Submit here: https://forms.gle/n1jg3eu1XardVxV28
    • Due by Mon (9/28) at 11:59pm

Justin

Justin Holman is CEO of Aftermarket Analytics, where he leads efforts to develop cutting edge sales forecasting and inventory optimization technology for the Automotive Aftermarket. Prior to joining Aftermarket Analytics, Justin managed corporate consulting for the Strategy & Analytics division at MapInfo Corporation, leading major projects for retail clients including The Home Depot, Darden Restaurants, Bridgestone-Firestone, Sainsbury’s and New York & Company. Before that, Justin served as Vice President of Software Development at LogicTools, now part of IBM's supply chain application software group. Justin holds a B.A. from Claremont McKenna College, a Ph.D. from the University of Oregon and an Executive Management certificate from Northwestern University's Kellogg School of Management.

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