Calendar
Note: future dates on this schedule are approximate and subject to change.
Binary data and logistic regression
- August 22
- Welcome to STA 712, Intro to logistic regression
- Slides
Textbook 4.2, 9.1, 9.2, 9.5
- August 24
- Fitting logistic regression models
- Slides
Textbook 4.4 - 4.8
- August 26
- Fitting logistic regression models, Fisher scoring
- Slides
Textbook 4.4 - 4.8
- Homework 1 released
- HW 1
- Challenge Assignment 1 released
- Challenge 1
Logistic regression diagnostics
- August 29
- Fisher scoring for logistic regression
- Slides
Textbook 4.4 - 4.8
- August 31
- Logistic regression assumptions and diagnostics
- Slides, Class activity
Textbook 8.3, 8.6, 8.7, 9.11
- September 2
- IRLS and influential points
- Slides, Class activity
Textbook 8.3, 8.4, 8.8
- Challenge Assignment 2 released
- Challenge 2
Logistic regression inference
- September 5
- Leverage and Cook’s distance
- Slides, Class activity
Textbook 8.3, 8.4, 8.8
- Homework 2 released
- HW 2
- Challenge Assignment 3 released
- Challenge 3
HW 1 due Tuesday
- September 7
- Multicollinearity and variance inflation factors
- Slides, Class activity
- September 9
- Properties of the MLE
- Slides
Textbook 4.9
Logistic regression inference
- September 12
- Wald tests
- Slides
Textbook 4.10, 7.2.1, 9.9
- September 14
- Wald tests
- Slides, Class activity
Textbook 4.10, 7.2
- Homework 3 released
- HW 3, Empirical logit plots
- Challenge Assignment 4 released
- Challenge 4
HW 2 due Thursday
- September 16
- Putting it all together
- Slides, Class activity, Solutions
Logistic regression inference
Logistic regression prediction
- September 26
- Confidence intervals
- Slides, Class activity, Solutions
- September 28
- Assessing predictions
- Slides
- Challenge Assignment 5 released
- Challenge 5
- September 30
- No class (weather)
HW 4 due
- Exam 1 released
- Exam 1
- Project 1 released
- Project 1
Beginning Poisson regression
- October 3
- Model selection
- Slides, Class activity
Textbook 4.12
- October 5
- Introduction to Poisson regression
- Slides
Textbook 5.2, 5.3, 5.5, 5.6, 10.1, 10.2
- October 7
- No class
Exam 1 due
Exponential dispersion models
- October 10
- Exponential dispersion models
- Slides
Textbook 5.2, 5.3, 5.5, 5.6
- October 12
- EDMs and goodness of fit
- Slides
Textbook 5.4, 10.5
Project 1 due
- Challenge Assignment 6 released
- Challenge 6
- October 14
- No class
Overdispersion
- October 17
- Goodness of fit and overdispersion
- Slides
Textbook 5.4, 6.8, 7.4
- HW 5 released
- HW 5
- October 19
- Overdispersion
- Slides
Textbook 5.4, 6.8, 7.4
- October 21
- No class Class activity, Solutions
Overdispersion
ZIP models
- October 31
- Negative binomial regression
- Slides, Class activity
Textbook 7.6, 10.5
- Challenge Assignment 7 released
- Challenge 7
- November 2
- Negative binomial, ZIP models
- Slides
- November 4
- ZIP models
- Slides, Class activity
- Challenge Assignment 8 released
- Challenge 8
- Project 2 released
- Project 2
ZIP models
Inference with ZIP models
- November 14
- Inference with ZIP models
- Slides, Class activity, R code
- November 16
- Beginning multinomial regression
- Slides
- November 18
- Fitting multinomial regression models
- Slides, Class activity
Exam 2 due
- Homework 7 released
- HW 7
Thanksgiving
- November 21
- Inference with multinomial regression
- Slides, Class activity
- November 23
- No class (Thanksgiving break)
Project 2 due
- November 25
- No class (Thanksgiving break)
Mixed effects
- November 28
- Intro to mixed effects
- Slides
- November 30
- Mixed effects models
- Slides
- December 2
- Mixed effects models
- Slides, Class activity