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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
<html>
<head>
<link rel="shortcut icon" href="icons/favicon_io/favicon-32x32.png" />
<link rel="stylesheet" type="text/css" href="assets/styles.css">
<link rel="stylesheet" href="assets/tabs-menu.css" type="text/css">
<title>
Topic schedule and lecture notes
</title>
</head>
<body>
<!-- this is now in assets/sched-table.css -->
<style type="text/css">
BODY {
background: white;
font-family: Arial, Helvetica, sans-serif;
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.tg .tg-week{text-align:center}
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font-size:14px;}
</style>
<center>
<ul class="basictab">
<li><a href="index.html">Home</a></li>
<li><a href="about.html">About</a></li>
<li><a href="resources.html"> Resources </a></li>
<li><a href="R/index.html">R Examples</a></li>
</ul>
</center>
<h2>Topic schedule and lecture notes</h2>
This table gives the schedule of lecture topics with links to lecture slides, readings, tutorials,
and associated R scripts illustrating these methods.
<ul>
<li>For convienence, I provide lecture slides in both single page and 4-up formats.</li>
<li>Readings from my book, <a href="https://www.taylorfrancis.com/books/mono/10.1201/b19022/discrete-data-analysis-michael-friendly-david-meyer"><cite>Discrete Data Analysis with R</cite></a> (DDAR) give pre-publication copies
of chapters. I do not allow them to be distributed further.</li>
<li>Readings from Agresti refer to Agresti (2019), <a href="https://www.wiley.com/en-us/An+Introduction+to+Categorical+Data+Analysis%2C+3rd+Edition-p-9781119405283"><cite>Introduction to Categorical Data Analysis, 3rd Ed.</cite></a></li>
<li>The R scripts show some of the examples from the lectures. They have been compiled with knitr,
<img src="icons/knitR.png" height="16" hspace="4" border="0">
so you can see the results.</li>
<li>Most <strong>Tutorials</strong> 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.</li>
<li>A tutorial in <tt>.Rmd</tt> form is an interactive document. Save it to your computer, open it in an RStudio
editor window and press "Run Document".</li>
</ul>
<table class="tg">
<tr>
<th class="head">Week</th>
<th class="head">Topic</th>
<th class="head">Readings</th>
<th class="head"><img src="icons/R.png" alt="R" width="16" height="16" hspace="4" align="left" border="0">R files <img src="icons/knitR.png" alt="knitR" height="16" hspace="4" align="right"
border="0"></th>
</tr>
<tr>
<td class="tg-week">1</td>
<td class="tg-cxkv">Overview [<a href="lectures/01-Overview.pdf">slides</a>]
[<a href="lectures/01-Overview-2x2.pdf">4up</a>]<br>
[<a href="lectures/RStudio.pdf">Working with R Studio</a>]
[<a href="lectures/RStudio-2x2.pdf">4up</a>]<br>
[<a href="tutorials/intro-to-R/intro-to-R.Rmd">intro-to-R.Rmd</a>]
</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter01.pdf">Ch1</a>,
<a href="VCDR/chapter02.pdf">Ch2</a>; <br/>
Agresti: Ch1</td>
<td class="tg-R">
<a href="tutorials/R-intro.R">R-into.R</a> [<a href="tutorials/R-intro.pdf"><img src="icons/knitR.png" alt="knitR" height="16" border="0"></a>]
</td>
</tr>
<tr>
<td class="tg-week">2</td>
<td class="tg-031e">Discrete distributions
[<a href="lectures/02-Discrete.pdf">slides</a>]
[<a href="lectures/02-Discrete-2x2.pdf">4up</a>]</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter03.pdf">Ch3</a> </td>
<td class="tg-R">
<a href="tutorials/R-data.R">R-data.R</a>
[<a href="tutorials/R-data.html"><img src="icons/knitR.png" alt="knitR" height="16" border="0"></a>]<br>
<a href="tutorials/binomial.R">binomial.R</a>
[<a href="tutorials/binomial.html"><img src="icons/knitR.png" alt="knitR" height="16" border="0"></a>]
</td>
</tr>
<tr>
<td class="tg-week">3</td>
<td class="tg-031e">Two-Way Tables: Independence & Association
[<a href="lectures/03-Twoway1.pdf">slides</a>]
[<a href="lectures/03-Twoway1-2x2.pdf">4up</a>]</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter04.pdf">Ch4</a>; <br/>
Agresti: Ch2</td>
<td class="tg-R">
<a href='R/berk-4fold.R'> berk-4fold.R</a>
[<a href='R/output/berk-4fold.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>] </a><br/>
<a href='R/vision-sieve.R'> vision-sieve.R</a>
[<a href='R/output/vision-sieve.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">4</td>
<td class="tg-031e">Two-Way Tables: Ordinal Data and Dependent Samples<br/>
[<a href="tutorials/twoway.pdf">Tutorial</a>] on two-way tables
</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter04.pdf">Ch4</a>; <br/>
Agresti: Ch2</td>
<td class="tg-R">
<a href='R/msdiag-agree.R'> msdiag-agree.R</a>
[<a href='R/output/msdiag-agree.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>] </a><br/>
<a href='R/haireye-spineplot.R'> haireye-spineplot.R</a>
[<a href='R/output/haireye-spineplot.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">5</td>
<td class="tg-031e">Loglinear Models and Mosaic Displays
[<a href="lectures/04-Loglin.pdf">slides</a>]
[<a href="lectures/04-Loglin-2x2.pdf">4up</a>]<br/>
[<a href="tutorials/loglin.pdf">Tutorial</a>] on loglin models;
[<a href="lectures/mosanimate.pdf">Mosaic display animation</a>]
</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter05.pdf">Ch5</a>; <br/>
Agresti: 2.7, Ch. 7</td>
<td class="tg-R">
<a href='R/berkeley-glm.R'> berkeley-glm.R</a>
[<a href='R/output/berkeley-glm.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a><br/>
<a href='R/titanic-loglin.R'> titanic-loglin.R</a>
[<a href='R/output/titanic-loglin.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">6</td>
<td class="tg-031e">Correspondence Analysis
[<a href="lectures/05-Corresp.pdf">slides</a>]
[<a href="lectures/05-Corresp-2x2.pdf">4up</a>] <br/>
[<a href="tutorials/corresp.pdf">Tutorial</a>] on CA;
</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter06.pdf">Ch6</a></td>
<td class="tg-R">
<a href='R/mental-ca.R'> mental-ca.R</a>
[<a href='R/output/mental-ca.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a><br/>
<a href='R/mca-presex3.R'> mca-presex3.R</a>
[<a href='R/output/mca-presex3.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">7</td>
<td class="tg-031e">Logistic Regression I
[<a href="lectures/06-Logistic.pdf">slides</a>]
[<a href="lectures/06-Logistic-2x2.pdf">4up</a>]<br/>
[<a href="tutorials/logistic.pdf">Logistic regression tutorial</a>]
</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter07.pdf">7.1-7.3</a>; <br/>
Agresti: 3.1-3.2; Ch 4
</td>
<td class="tg-R">
<a href='R/arthritis-logistic.R'> arthritis-logistic.R</a>
[<a href='R/output/arthritis-logistic.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>] </a> <br>
<a href='R/cowles-logistic.R'> cowles-logistic.R</a>
[<a href='R/output/cowles-logistic.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a> <br>
<a href='R/Arrests-logistic.R'> Arrests-logistic.R</a>
[<a href='R/output/Arrests-logistic.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">8</td>
<td class="tg-031e">Logistic Regression II
[<a href="lectures/07-Logistic2.pdf">slides</a>]
[<a href="lectures/07-Logistic2-4up.pdf">4up</a>]</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter07.pdf">7.3-7.4</a>; <br/>
Agresti: Ch 4-5</td>
<td class="tg-R">
<a href='R/cowles-effect.R'> cowles-effect.R</a>
[<a href='R/output/cowles-effect.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>] </a> <br>
<a href='R/Arrests-effects.R'> Arrests-effects.R</a>
[<a href='R/output/Arrests-effects.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a> <br>
<a href='R/berkeley-diag.R'> berkeley-diag.R</a>
[<a href='R/output/berkeley-diag.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a> <br>
</td>
</tr>
<tr>
<td class="tg-week">9</td>
<td class="tg-031e">Multinomial Logistic Regression
[<a href="lectures/07-Logistic2.pdf">slides</a>]
[<a href="lectures/07-Logistic-2x2.pdf">4up</a>]</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter08.pdf">8.2-8.3</a>; <br/>
Agresti: Ch 6</td>
<td class="tg-R">
<a href='R/arthritis-propodds.R'> arthritis-propodds.R</a>
[<a href='R/output/arthritis-propodds.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>] </a> <br>
<a href='R/wlf-nested.R'> wlf-nested.R</a>
[<a href='R/output/wlf-nested.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a> <br>
<a href='R/wlf-glogit.R'> wlf-glogit.R</a>
[<a href='R/output/wlf-glogit.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">10</td>
<td class="tg-031e">Log-Linear Models I
[<a href="lectures/08-Loglin2.pdf">slides</a>]
[<a href="lectures/08-Loglin2-2x2.pdf">4up</a>]</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter08.pdf">9.1-9.4</a>; <br/>
Agresti: Ch 7</td>
<td class="tg-R">
<a href='R/berkeley-logit.R'> berkely-logit.R</a>
[<a href='R/output/berkeley-logit.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">11</td>
<td class="tg-031e">Log-Linear Models II
[<a href="lectures/08-Loglin2.pdf">slides</a>]
[<a href="lectures/08-Loglin2-2x2.pdf">4up</a>]<br/>
[<a href="tutorials/glm-ordinal.pdf">Ordinal factors tutorial</a>]
</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter08.pdf">Ch 10</a>; <br/>
Agresti: Ch 8</td>
<td class="tg-R">
<a href='R/mental-glm.R'> mental-glm.R</a>
[<a href='R/output/mental-glm.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</td>
</tr>
<tr>
<td class="tg-week">12</td>
<td class="tg-031e">Generalized Linear Models: Count Data
[<a href="lectures/09-CountData.pdf">slides</a>]
[<a href="lectures/09-CountData-2x2.pdf">4up</a>] <br/>
[<a href="tutorials/count-data.pdf">Count data GLMs tutorial</a>]
</td>
<td class="tg-031e">DDAR:
<a href="VCDR/chapter09.pdf">Ch 11</a>; <br/>
Agresti 3.3-3.5</td>
<td class="tg-R">
<a href='R/phdpubs.R'> phdpubs.R</a>
[<a href='R/output/phdpubs.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a><br>
<a href='R/quine.R'> quine.R</a>
[<a href='R/output/quine.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>]</a>
</tr>
<tr>
<td class="tg-week">13</td>
<td class="tg-031e">Generalized Linear Models: Further topics
[<a href="lectures/10-Log-Odds.pdf">slides</a>]
[<a href="lectures/10-Log-Odds-2x2.pdf">4up</a>]
</td>
<td class="tg-031e">CARME2015:
<a href="https://www.datavis.ca/papers/CARME2015-2x2.pdf">slides</a></td>
<td class="tg-R">
<a href='R/hospvisits-logodds.R'> hospvisits-logodds.R</a>
[<a href='R/output/hospvisits-logodds.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>] </a> <br>
<a href='R/mice-ex.R'> mice-ex.R</a>
[<a href='R/output/mice-ex.html'><img src='icons/knitR.png' alt='knitR' height=16 border=0>] </a>
</td>
</tr>
</table>
</body>
</html>