Lesson 8: Categorical Data and Indicator Variables

October 21, 2026

Review:

  • Multicollinearity
  • Interaction Variables
  • Exam 2 on Wed 28 Oct – focus on Multiple Regression, more to follow

Presentation:

  • Pivot tables to aggregate by category
  • Indicator Variables (aka “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 the estimate
  • Demonstration with Sample Real Estate data
    • Use a Pivot table to summarize price by neighborhood
    • create a dummy variable for a neighborhood
    • create a dummy variable for multiple neighborhoods

Activity:

  • Use the Pueblo Real Estate model (from last lesson)
    • Incorporate one or more Indicator variables
    • Use an indicator variable to represent high cost or low cost neighborhoods
    • Can you improve R^2 and/or F with an indicator variable?

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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