ReferenceTexts

This year we will be using A First Course in Bayesian Statistical Analysis by Peter Hoff as a primary text for this course (Required).

The book Bayesian Computation with R, by Jim Albert is also recommended.

The BUGS website has many examples for Bayesian analysis using winbugs. If you are unfamiliar with classical methods for data analysis you may wish to purchase Statistical Analysis and Data Display by Richard Heiberger and Burt Holland. For those students going on in statistics this covers many topics that we will not have time to touch on, but often come up in consulting. The Statistical Sleuth by F. Ramsey and D. Schafer published by Duxbury covers a range of topics and applications in data analysis. While written at a lower mathematical level, lots of interesting dataset and applications. There are many introductory statistics texts that cover essentially the same range of basic probability theory and statistical models and methods that are assumeds as a pre/co-requisite for this class. Statistical Inference by George Casella and Roger Berger 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.) These texts will be available in the SECC.

We will use the R programming language for this class, I suggest

For students in DSS, I strongly recommend that you purchase a reference book LaTeX. Some suggestions are:

For students outside of statistics, LaTeX is not required but I will expect that you will be able to use a word processor that can include graphics and that can typeset equations.

Please 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.