Chapter 10 – Contents

1. Preface
2. Multiple regression: why and when?
3. Multiple linear regression with two explanatory variables
4. Multiple regression and simple regression: Omitted variable bias
5. A1 Case Study -- Understanding the gender difference in earnings
6. Multiple linear regression terminology
7. Standard errors and confidence intervals in multiple linear regression
8. Hypothesis testing in multiple linear regression
9. A2 Case Study -- Understanding the gender difference in earnings
10. Multiple linear regression with three or more explanatory variables
11. Nonlinear patterns and multiple linear regression
12. A3 Case Study -- Understanding the gender difference in earnings
13. Qualitative right-hand-side variables
14. A4 Case Study -- Understanding the gender difference in earnings
15. Interactions: Uncovering different slopes across groups
16. A5 Case Study -- Understanding the gender difference in earnings
17. Multiple regression and causal analysis
18. A6 Case Study -- Understanding the gender difference in earnings
19. Multiple regression and prediction
20. B1 Case Study -- Finding a good deal among hotels with multiple regression
21. Summary and practice
22. Under the hood: A two-step procedure to get the multiple regression coefficient
23. References and further reading