• binomial.ps -- first two pages discussed on 8/30
• eda.S -- EDA notes from 9/4 and 9/6
• eggs.S -- EDA notes from 9/11
• inference.ps -- inference notes from 9/13
• binomial.ps -- slides on binomials/proportions for 9/13 and 9/18
• prop.demo.S -- S code from 9/13
• binom.S -- S code from 9/18
• binomrank.ps -- slides on posterior ranks via simulation, hierarchical models, and Q-Q plots from 9/20
• binomrank.S -- S code on binomial ranks from 9/20
• hierarch.S -- S code on Q-Q plots from 9/25
• regression.ps -- slides on simple linear regression from 9/25 and 9/27
• regression.S -- S code from 9/25 and 9/27 (REVISED 9/26)
• multregr.ps -- slides on multiple linear regression from 10/2 and 10/4
• multregr.S -- S code from 10/2 and 10/4
• Cintro.ps -- slides on introductory C programming from 10/9, 10/11, and 10/18
• mcmc.ps -- slides on Markov chain Monte Carlo, using multiple source files (e.g., a file of random number generators), and other useful things (top, nice, background) from 10/25, 10/30, and 11/1
• mcmc.normal.S -- the associated S code for the MCMC normal and VA examples from 10/25, 10/30, and 11/1
• mcmcanova.ps -- slides on Bayesian ANOVA from 11/6
• memory.ps -- slides on dynamic memory allocation, pseudo-dynamic memory allocation using gcc, and using qsort() from 11/6
• fortran.ps -- slides on calling fortran routines, especially ones from IMSL, BLAS, and LAPACK from 11/8
• fortran.code -- sample C code for calling routines from IMSL, BLAS, and LAPACK from 11/8 (despite the name of this file, all the code is actually in C)
• multnorm.ps -- slides on generating random multivariate normals and doing Bayesian linear regression from 11/13
• unix.ps -- slides on various useful unix commands from 11/15
• machines.ps -- slides on some aspects of how computers work from 11/27
• latex.ps -- slides on Slitex and Bibtex from 11/27
• Latex files -- files from 11/27, demonstrating Slitex, Bibtex, and a Duke thesis format

All of the C code from class examples can be found here

Problems of Proportions -- Supplementary reading courtesy of Mike West

Linear Regression -- More supplementary reading courtesy of Mike West

The V.A. research project report