Topic schedule and lecture notes

This table gives the schedule of lecture topics with links to lecture slides, readings, tutorials, and associated R scripts illustrating these methods.

For convienence, I provide lecture slides in both single page and 4-up formats.
Readings from my book, Discrete Data Analysis with R (DDAR) give pre-publication copies of chapters. I do not allow them to be distributed further.
Readings from Agresti refer to Agresti (2019), Introduction to Categorical Data Analysis, 3rd Ed.
The R scripts show some of the examples from the lectures. They have been compiled with knitr, so you can see the results.
Most Tutorials are are provided in PDF form. Sometimes there is a linked R script you can use to save some typing. Another way to do them is to open the file in one window and copy & paste code lines into an R script in an RStudio editor window.
A tutorial in .Rmd form is an interactive document. Save it to your computer, open it in an RStudio editor window and press "Run Document".

Week	Topic	Readings	R files
1	Overview [slides] [4up] [Working with R Studio] [4up] [intro-to-R.Rmd]	DDAR: Ch1, Ch2; Agresti: Ch1	R-into.R []
2	Discrete distributions [slides] [4up]	DDAR: Ch3	R-data.R [] binomial.R []
3	Two-Way Tables: Independence & Association [slides] [4up]	DDAR: Ch4; Agresti: Ch2	berk-4fold.R [] vision-sieve.R []
4	Two-Way Tables: Ordinal Data and Dependent Samples [Tutorial] on two-way tables	DDAR: Ch4; Agresti: Ch2	msdiag-agree.R [] haireye-spineplot.R []
5	Loglinear Models and Mosaic Displays [slides] [4up] [Tutorial] on loglin models; [Mosaic display animation]	DDAR: Ch5; Agresti: 2.7, Ch. 7	berkeley-glm.R [] titanic-loglin.R []
6	Correspondence Analysis [slides] [4up] [Tutorial] on CA;	DDAR: Ch6	mental-ca.R [] mca-presex3.R []
7	Logistic Regression I [slides] [4up] [Logistic regression tutorial]	DDAR: 7.1-7.3; Agresti: 3.1-3.2; Ch 4	arthritis-logistic.R [] cowles-logistic.R [] Arrests-logistic.R []
8	Logistic Regression II [slides] [4up]	DDAR: 7.3-7.4; Agresti: Ch 4-5	cowles-effect.R [] Arrests-effects.R [] berkeley-diag.R []
9	Multinomial Logistic Regression [slides] [4up]	DDAR: 8.2-8.3; Agresti: Ch 6	arthritis-propodds.R [] wlf-nested.R [] wlf-glogit.R []
10	Log-Linear Models I [slides] [4up]	DDAR: 9.1-9.4; Agresti: Ch 7	berkely-logit.R []
11	Log-Linear Models II [slides] [4up] [Ordinal factors tutorial]	DDAR: Ch 10; Agresti: Ch 8	mental-glm.R []
12	Generalized Linear Models: Count Data [slides] [4up] [Count data GLMs tutorial]	DDAR: Ch 11; Agresti 3.3-3.5	phdpubs.R [] quine.R []
13	Generalized Linear Models: Further topics [slides] [4up]	CARME2015: slides	hospvisits-logodds.R []