Chapter Summary

Multiple regression is the appropriate statistical measure of association between interval-level variables controlling for one or more other interval-level variables. It gives us a multiple dimensional equation for a line that parses out the impact of each independent variable on the dependent variable controlling for all of the others. The entire model has a single constant, and each independent variable has its own unstandardized coefficient, standard error, standardized coefficient, and statistical significance. In addition, the entire model has a single R2.

Learning Objectives

After reading this chapter, you should:

  • Understand the assumptions made in calculating ordinary least squares regression
  • Understand how violations of those assumptions can affect the results
  • Be familiar with techniques for coping with the violations of the Gauss-Markov assumptions
  • Be able to complete a three step analysis of a multiple regression
  • Know how to create dummy variables in SPSS
  • Know how to get scatter plots in SPSS
  • Know how to produce residual scatter plots in SPSS