Bayesian Statistics and Computing

Software and dataset tips:

R can be obtained and installed from www.r-project.org/. That site has many pointers for using R, and programming in it.

A nicely packaged version of R can also be obtained from www.rstudio.org.

The University also has a campus license for Matlab.

The list of resources specifically for learning and using R is at: https://stats.idre.ucla.edu/r/

Coursera has a 4-week introductory course on R computing: taught by Prof. Roger Peng from Johns Hopkins University. The sessions are monthly.

There are also numerous R books and tutorials, for example:

R in Action by R. Kabacoff
Quick-R site by the R. Kabacoff, based on the "R in Action" book
Data Analysis and Graphics Using R by J. Maindonald
simpleR, by J.Verzani
R Tutorial by C. Yau

A collection of many datasets, from a variety of books and websites, can be found at: http://www.statsci.org/datasets.html

Some datasets and R code from our books (by Christian Robert), can be found online at the book website, and at the author's website.