Lesson 8: Multiple Regression Variable Selection Procedures

February 13, 2019

Review:

• Intro to Multiple Regression
• Portfolio scores
  • Portfolio Example
• Exam 1 Retake

Presentation:

• Variable Selection Procedures
  • Variable Selection
  • Backward Elimination then Forward Selection
  • Demonstrate with East Pueblo RE Sales 2014-2016
• F-Statistic
• Modeling Objective:
  • Achieve highest R^2 possible
    • For some data this may be below 0.50
    • Don’t sacrifice too much significance for small gains in R^2
  • Achieve high F-statistic
    • Fewer variables = generally preferable (keep it simple)
    • Significance of F (p-value) should be <0.05, lower is better
    • Individual variables should have p-value < 0.05
    • Occasionally it’s appropriate to make exceptions

Assignment (complete by Monday):

• Produce a model to estimate MLB winning percentage
  • Use 2013 MLB Team statistics
  • Test all variables using one or more of the selection procedures above
  • Produce a Final Model, aiming to maximize R^2 and F-Statistic
  • Add to your portfolio