Math 33110: Applied Regression Analysis
Course Description
This is an undergraduate-level course for students majoring in statistics, probability, or any other field where applied statistics plays an
essential role. Methodology and theory for linear regression will be introduced, illustrated by examples and applications. Extensions and advanced
topics, such as categorical predictors, polynomial regression, analysis of variance, weighted least squares, mixed models, transformations,
regression diagnostics, variable selection, nonlinear regression, and generalized linear models, will be covered if time permits. The course will
include intensive writing and programming components.
Syllabus
Final Exam and Project
Final exam: Wednesday, June 22, 2:00–4:00 pm, 102 Classroom Building 2
Final project: Problems, due Friday, June 24
Office hours in the final week: Tuesday, June 21, 2:00–4:00 pm
Lectures and Assignments
Note: W below stands for Weisberg and SL for Seber & Lee.
| Week | Date | Topics | References | Assignments | Further Reading |
| 1 | February 22 | Scatterplots and regression | W Chapter 1 | W Problems 1.2, 1.4, 1.6 | Cleverland, Diaconis & McGill (1982) |
| February 24 | Scatterplots and regression
Simple linear regression | W Chapter 1
W Sections 2.1–2.3 | W Problems 2.2, 2.4 | Friendly & Denis (2005) |
| 2 | March 2 | Simple linear regression | W Sections 2.4–2.6 | W Problems 2.8, 2.10.1–4, 2.12, 2.14, 2.18 | |
| 3 | March 7 | Simple linear regression
Multiple regression | W Sections 2.7–2.8
SL Section 3.1 | | |
| March 9 | Multiple regression | SL Sections 3.2–3.4
W Chapter 3 | W Problems 2.20, 3.2, 3.4, 3.7 (errata)
SL Exercise 3b.4 | Aldrich (2005) |
| 4 | March 16 | Interpretation of main effects | W Section 4.1 | W Problems 4.2, 4.4, 4.8, 4.9 | |
| 5 | March 21 | Interpretation of main effects | W Sections 4.2–4.5 | W Problems 4.10, 4.12 | Greenland, Robins & Pearl (1999), Gelman & Meng (1991) |
| March 23 | Complex regressors | W Sections 5.1–5.2 | W Problems 5.4, 5.5, 5.6 | Morrissette & McDermott (2013) |
| 6 | March 30 | Complex regressors | W Sections 5.3–5.5 | W Problems 5.8, 5.9, 5.14, 5.17, 5.18 | Tarpey & Holcomb (2000) |
| 7 | April 4 | No class | | | |
| April 6 | Complex regressors | W Sections 5.6
SL Section 3.8 | SL Exercises 3g.1, 3g.2 | Heitjan & Basu (1996), Carpenter, Kenward & Vansteelandt (2006) |
| 8 | April 13 | Midterm | | | |
| 9 | April 18 | Hypothesis testing and ANOVA | W Sections 6.1–6.3
SL Secion 4.2 | | |
| April 20 | Hypothesis testing and ANOVA | SL Sections 4.3 and 8.2 | W Problems 6.4, 6.8, 6.10
SL Exercise 4b.5 | |
| 10 | April 27 | Hypothesis testing and ANOVA | W Sections 6.4–6.6 | W Problems 6.14, 6.16 | Harvey, Liu & Zhu (2016) |
| 11 | May 2 | No class | | | |
| May 4 | No class | | | |
| 12 | May 11 | General variances | SL Section 3.10
W Sections 7.1–7.3 | SL Exercises 3k.3, 3k.4
W Problems 7.2, 7.6.1–4 | |
| 13 | May 16 | General variances | W Sections 7.4–7.7 | W Problems 7.10, 7.12 | |
| May 18 | Transformations | W Chapter 8 | W Problem 8.5 | |
| 14 | May 25 | Regression diagnostics | W Chapter 9 | W Problems 9.2, 9.4, 9.6, 9.11, 9.16 | |
| 15 | May 30 | Variable selection | W Chapter 10 | | Yang (2005) |
| June 1 | Variable selection
Nonlinear regression | W Sections 10.2.3 and 10.3.1
W Chapter 11 | W Problems 10.3, 10.6, 11.2 | |
| 16 | June 8 | Binomial and Poisson Regression | W Chapter 12 | W Problems 12.7, 12.9 |
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