Reference Texts

We will follow use Statistical Analysis and Data Display by Richard Heiberger and Burt Holland. as a primary text this semester, with supplemental readings/handouts on Bayesian inference. Online files and errata from HH.

I also suggest a book for learning R.

• An Introduction to R (PDF file at CRAN), based on the former "Notes on R", gives an introduction to the language and how to use R for doing statistical analysis and graphics. You may print out the pdf file or view the contents online. Paper back available at Amazon.
  
• Data Analysis and Graphics Using R by J. Maindonald and J. Braun. Introduction to modelling and computing in R covers more advanced statisical modeling than An Introduction to R.
  
• Modern Applied Statistics with S by Venables and Ripley. Programming and statistical modeling in both R and S-Plus.

For datasets and statistical analyses with more interpretation, I recommend:

• The Statistical Sleuth by F. Ramsey and D. Schafer published by Duxbury. This cover a range of topics and applications in data analysis. While written at a lower mathematical level, lots of interesting dataset and applications.
  

You may want to purchase a book on Bayesian inference. Here are three of varying degrees of difficulty::

• Introduction to Bayesian Statistics by William Bolstad. Covers introductory statistics from a Bayesian perspective. Covers normal, binomial, two-sample problems up to simple linear regression. Useful background material to supplement course notes.
  
• Applied Bayesian Modelling by Peter Congdon published by Wiley. This provides an introduction to applied Bayesian modelling and is companion book to Congdon's Bayesian Statistical Modeling (Wiley 2001). Useful as a reference for more advanced modelling beyond the scope of this course.
  
• Bayesian Data Analysis by Andrew Gelman, John B Carlin, Hal S Stern and Don B Rubin, published by CRC Press. This provides an introduction to Bayesian analysis, and continues with more advanced statistical modelling that goes beyond the scope of this course, but it is another excellent text for both statistical modelling and applications, is full of good reading on concepts, and has many examples. This is now in the second edition.
  
• The BUGS website has many examples for Bayesian analysis using winbugs.
  
• List of probability distributions and updating expressions for prior/posteriors (will be updated as we go along)

There are many introductory statistics texts that cover essentially the same range of basic probability theory and statistical models and methods. A couple of really good ones you might consult from time to time are noted below. In addition, a lot of relevant material at an introductory level is available in some of the notes -- much won't be explictly covered, but you should find lots of the material there useful and it is easy to browse.

• Statistics by Michael Lavine (pdf pre-print of around 250 pages) This is used in the corequisite class STA213. We will refer to these notes for more theoretical bacground to supplement material the The Statistical Sleuth
  
• Statistical Inference by George Casella and Roger Berger. This is used in STA213. We will refer to it from time to time for basic distribution theory and classical inference (recommended, if you do not already have a copy, but other basic probability and statistics texts can be substituted.)
  

It is strongly recommended that you purchase a reference book LaTeX. Some suggestions are:

• LATEX: A Document Preparation System -- User's Guide and Reference Manual by Leslie Lamport, published by Addison-Wesley. 2nd Edition. This is my favorite, but many other LaTeX guides are equally good and are essentially exchangeable. For example,
• The LaTeX Companion by M Goossens, F Mittelbach and A Samarin, published by Addison-Wesley. I use this one too
• A Guide to LaTeX -- Document Preparation for Beginners and Advanced Users by H. Kopka and P. Daly, published by Addison-Wesley. Another popular guide to LaTeX.
• Math into LaTeX -- An Introduction to LaTeX and AMS-LaTeX by George Gratzer, published by Birkhauser. Still yet another LaTeX book.
  

Check the computing page for additional links to support material on unix, using emacs with LaTeX ,R, and S-Plus, plus other infomations for running R, S-Plus, etc.