Additional textbook references:
The following book is free to download on link.springer.com if you're
accessing it on UCI campus:
The following books are available for preview on link.springer.com:
The following textbooks are on reserve in the UCI Science
Library:
Lecture: Tue/Thurs 12:30-1:50pm DBH 1500
Lab: Wed 4:00-4:50pm DBH 1500
| Instructor |
| Stacey Hancock,
PhD |
| Office: 2204 DBH |
| Phone: (949) 824-9795 |
| Email: stacey.hancock_at_uci.edu |
| Office Hours: Tue/Thurs 10:00-11:30am or by appointment. |
Download and Install R:
This calendar will be updated after each class. Check back
periodically for required reading, additional handouts and
references, homework assignments, and lecture notes.
| Date |
Material
Covered (Tentative schedule; may be updated after each class) |
Date HW Due |
Assignment |
| Week 1: |
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| Tue. Jan. 8 |
Lecture
1 Notes Chapter 1, Sections 1.1-1.3 (Skip 1.4 for now): categorical response data, binomial and multinomial distributions, review of inference for a single population proportion.
|
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| Discussion 1 |
Introduction/review
of R software. R code used in discussion. |
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| Thurs. Jan. 10 |
Lecture
2 Notes Chapter 2, Sections 2.1-2.3: probability structures of contingency tables, comparing two proportions, relative risk, and odds ratio. |
Fri. Jan. 18 by 5pm |
Homework #1 |
| Week 2: |
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| Tue. Jan. 15 |
Lecture
3 Notes Finish Lecture 2 notes on inference for odds ratio. Chapter 2, Sections 2.4 and 2.6 (Skip 2.5 and 2.7 for now): inference for two-way contingency tables. |
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| Discussion 2 |
Discussion Slides Discussion R code Review of sampling distributions, confidence intervals, and hypothesis tests. |
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| Thurs. Jan. 17 |
Finish Lecture 3 notes (and Lecture 2 R code)
on tests of independence. |
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| Week 3: |
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| Tue. Jan. 22 |
Lecture
4 Notes Start Chapter 3; review ordinary least squares.
|
Thurs. Jan. 31 |
Homework #2 (Updated at 11:45pm on Sat. Jan. 26) |
| Discussion 3 |
Matrix algebra in R
using CPS data. R code used in discussion. |
||
| Thurs. Jan. 24 |
Lecture
5 Notes (updated Tue. Jan. 29) Finish Lecture 4 notes and World Bank data example; Chapter 3, Sections 3.1-3.2: components of GLMs and GLMs for binary data. |
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| Week 4: |
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| Tue. Jan. 29 |
Lecture
6 Notes Finish Lecture 5 notes on GLMs for binary data; Chapter 3, Section 3.3: GLMs for count data.
|
Tue. Feb. 5 |
Homework #3 |
| Discussion 4 |
No discussion this week; Prof. Hancock will
have office hours during discussion time. |
||
| Thurs. Jan. 31 |
Lecture
7 Notes Finish Lecture 6 notes; Chapter 3, Section 3.4 (Skip Section 3.5): statistical inference and model checking for GLMs. |
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| Week 5: |
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| Tue. Feb. 5 |
Lecture
8 Notes Leftovers from Chapter 3; Chapter 4, Sections 4.1-4.5. |
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| Discussion 5 |
Review for Midterm Exam. |
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| Thurs. Feb. 7 |
MIDTERM EXAM Midterm Information, Material, and Practice Problems Solutions to Practice Problems Midterm Exam Solutions |
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| Week 6: |
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| Tue. Feb. 12 |
Lecture
9 Notes Finish Lecture 8 notes; Chapter 4, Sections 4.3.4-4.3.5 on Cochran-Mantel-Haenszel and Breslow-Day tests. |
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| Discussion 6 |
Hand back and go over Midterm exam. |
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| Thurs. Feb. 14 |
Lecture 10
Notes Finish Lecture 9 notes; Chapter 5, Sections 5.1-5.2 on model selection and model checking (Skip Sections 5.3-5.5). |
Fri. Feb. 22 by 5pm |
Homework #4 (Updated Sun. Feb. 17) Color Options in R Point Character Options in R |
| Week 7: |
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| Tue. Feb. 19 |
Lecture 11
Notes More examples on model checking and model diagnostics. |
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| Discussion 7 |
More practice
with plotting in R. R code used in discussion. |
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| Thurs. Feb. 21 |
Lecture 12
Notes Addendum to Lecture 12 Notes Finish Moth data example; Chapter 7, Section 7.1 on loglinear models; revisit Chapter 2, Section 2.7 on association in three-way tables (Skip Chapter 6 on multicategory logit models for now). |
Fri. Mar. 1 by 5pm |
Homework #5 |
| Week 8: |
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| Tue. Feb. 26 |
Finish Lecture 12 notes. |
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| Discussion 8 |
No discussion this week; Prof. Hancock will
have office hours during discussion time. |
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| Thurs. Feb. 28 |
Lecture 13
Notes Chapter 7, Section 7.2. |
Fri. Mar. 8 |
Homework #6 |
| Week 9: |
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| Tue. Mar. 5 |
Lecture
14 Notes Finish housing example (loglinear models for higher-dimension tables); Section 7.3; additional material on overdispersion.
|
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| Discussion 9 |
No discussion this week; Prof. Hancock will
have office hours during discussion time. |
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| Thurs. Mar. 7 |
Lecture
15 Notes Finish Lecture 14 notes; negative binomial regression. |
Tue. Mar. 19 by 6pm |
Take-home final exam handed out at the end of lecture. |
| Week 10: |
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| Tue. Mar. 12 |
Lecture 16
Notes Additional notes on equivalencies between odds ratios. Section 5.5 on sample size and power; Section 6.1 on multinomial logistic regression. |
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| Discussion 10 |
No discussion this week. |
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| Thurs. Mar. 14 |
Lecture 17
Notes Finish Lecture 16 notes; Section 6.2 on proportional odds models. Additional references:
|
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| Final Exam: |
Due by 6pm,
Tue. Mar. 19. Description of CHD data for Problem 4 of the final exam: chd_description.pdf Final Exam Solutions AIC Winners for Problem 4 (Disclaimer: AIC is not the only criteria for a good model!) Final Exam Grading Information |
Homework solutions will be posted the evening homework is due
(or early the next morning).