Regression Analysis

This class is all about applying regression analysis and linear models, including generalized linear models, mediation and moderation, with a little bit of machine learning techniques thrown in. The book we’ll use throughout the class, and that drives the structure of the lecture slides, is Regression Analysis and Linear Models by Richard Darlington and Andrew Hayes. This course uses R and RStudio for all data analyses.

A subset of the General Social Survey data set, a data set used in Quas et al. about high risk youth data set, and a data set regarding poverty, violence, and teen birth rates per state will be used in the examples. We will also pull from FiveThirtyEight’s open data on GitHub occassionally throughout the class (many of these data sets can be used for your class project as well if they have both continuous and categorical predictors). Finally, a small (ficticious) data set about The Office (US) and Parks and Recreation television shows is also available.


Lecture Slides

  1. Introductions to the class PPTX or PDF and to R and RStudio HTML or RMD and Chapter 1 PPTX or PDF
  2. Chapter 2 PPTX or PDF
  3. Chapter 3 PPTX or PDF
  4. Chapter 4 PPTX or PDF
  5. Chapter 5 PPTX or PDF
    • Examples HTML or RMD
    • Review Material for Exam 1: PPTX and PDF
    • Me, trying to explain why the slope changes when you control for a variable related to both X and Y while the correlation changes if the control variable is related to Y: VennDiagram.mp4
    • Why Correlation Changes When Slope Doesn’t Sometimes When Controlling: PPTX and PDF
  6. Chapter 6 PPTX or PDF
  7. Chapter 7 PPTX or PDF
  8. Chapter 8 PPTX or PDF
  9. Chapter 9 and 10 PPTX or PDF
  10. Chapter 11 PPTX or PDF
  11. Chapter 12 PPTX or PDF
  12. Chapter 13 and 14 PPTX or PDF
  13. Chapters 16 and 17 PPTX or PDF
  14. Chapter 18 PPTX or PDF
  15. Chapter 15 HTML

Homework Assignments

Homework HTML (Easier to Read) RMD (To Work With)
Final Project HTML Example Final Project PDF and Word