Chapter 3 - Multiple Regression

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Lecture Slides:    Powerpoint     PDF

Learning Objectives

  • Derive the OLS estimator of the regression coefficients when there are two or more right-hand variables in the model
  • Fit a multiple regression model using the least-squares criterion
  • Identify the conditions under which a multiple regression estimate is the same as the simple regression estimate
  • Interpret a multiple regression coefficient

Examples

What We Learned

  • How to solve the least-squares problem to fit a multiple regression model.
  • Multiple regression estimates differ from simple regression estimates if the right-hand-side variables are correlated with each other.
  • How to apply the multiple regression least-squares formula using a spreadsheet.
  • How to interpret a multiple regression coefficient
  • R-squared increases when you add an X variable to a model