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