Recommended Books

[wpress]

There is no required text. However, many lectures will utilize methods in Numerical Recipes, Third Edition. Enrolled students will be provided with a free electronic subscription to this book, as well as access to its source code.

Some other relevant books, roughly in priority order, are:

Bishop, Pattern Recognition and Machine Learning
Closest book that I know of to the spirit of this course, although the order of presentation is quite different.

Hastie, Tibshirani, and Friedman, The Elements of Statistical Learning
Probably the best-selling book in machine learning.

Gelman et al., Bayesian Data Analysis

Ewens and Grant, Statistical Methods in Bioinformatics

Givens and Hoeting, Computational Statistics

Wasserman, All of Statistics
This is a good book for learning the "jargon" of the statistics literature.

[wpress]

A good book on both the fundamentals of Bayesian thinking and applications is

Sivia and Skilling, Data Analysis: A Bayesian Tutorial
http://www.amazon.com/Data-Analysis-...dp/0198568320/

I actually haven't yet seen this new edition, but I expect it is at least as good as the earlier edition that I own,
http://www.amazon.com/Data-Analysis-.../dp/0198518897

[owlgorithm]

"The Structures of Life" is a very good introduction to biological molecules for those who are interested. It's free and available from the NIH website:

http://publications.nigms.nih.gov/structlife/

It has really good illustrations---and really, who doesn't like pretty pictures?

[johnwoods]

Most of the books on this list are checked out and aren't due until June 10th.

If anyone needs "Statistical Methods in Bioinformatics, 2nd Ed" and "Bayesian Data Analysis, 2nd Ed," I have these, and you're welcome to come study with me.

I also have a photocopy of "Probability, Frequency, and Reasonable Expectation" by R.T. Cox. The book isn't currently checked out (I couldn't tell if it was reference), but if you get desperate, email me.

John
john.o.woods (gmail)