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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.

Syllabus

Class Materials

Unit 1

Chapter Slides and Materials Recorded Lecture Examples
Intro to the class PPTX & PDF Recorded Lecture  
Intro to R and RStudio HTML & RMD Recorded Lecture  
Chapter 1 PPTX & PDF Recorded Lecture Examples
  Tidy Data & Data Guidelines    
Chapter 2 PPTX & PDF Recorded Lecture Examples
  Plot Your Data    
Chapter 3 PPTX & PDF Recorded Lecture Examples
Chapter 4 PPTX & PDF Recorded Lecture Examples
Chapter 5 PPTX & PDF Recorded Lecture Examples & Review 1 & Review 2 & Review 3
Chapter 6 PPTX & PDF Recorded Lecture Examples

Unit 2

Chapter Slides and Materials Recorded Lecture Examples
Chapter 7 PPTX & PDF Recorded Lecture Examples
Chapter 8 PPTX & PDF Recorded Lecture Examples
Chapter 9 and 10 PPTX & PDF Recorded Lecture Examples
Chapter 11 PPTX & PDF Recorded Lecture Examples

Unit 3

Chapter Slides and Materials Recorded Lecture Examples
Chapter 12 PPTX & PDF Recorded Lecture Examples
Chapters 13 and 14 PPTX & PDF Recorded Lecture Examples & Review Material
Chapters 16 and 17 PPTX & PDF Recorded Lecture & Causation and Linear Models Examples
  Measurement/Reproducibility & Measurement Error & Missing Data - see Little, R. J., & Rubin, D. B. (2014). Statistical analysis with missing data (Vol. 333). John Wiley & Sons. & Missing Data Overview   Resampling Examples

Unit 4

Chapter Slides and Materials Recorded Lecture Examples
Chapter 18 PPTX & PDF Recorded Lecture & What Are The Odds? Examples
Chapter 15 HTML Recorded Lecture Examples

Homework Assignments

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