This page, updated throughout the course, will feature slides from our sessions, and examples for you to try.
Prior to the module, please install up-to-date versions of R and RStudio on the laptop you will use during the summer institute. Both are free.
- R is available from this list of sites.
- RStudio is available here.
- Stan: Windows users first need the Rtools toolchain, Mac users may need the toolchain and corresponding tools. Then install R's rstan package.
- JAGS: Download and install JAGS itself , then install R's rjags package
- INLA: To get the INLA package for R, follow the non-standard procedure here
- WinBUGS: you will need WinBUGS and the R2WinBUGS R package. Note making WinBUGS work on a Mac requires a package manager such as HomeBrew, and you may prefer just to use JAGS instead.
Script files are posted following each session; these will contain our R code for the exercises. To make them work on your computer, remember to modify file names and locations appropriately. Also note that many different 'correct' solutions are possible. All times/dates are Pacfic, i.e. Seattle time.
The module has 10 sessions, each of 80 minutes. The standard format for a session is approximately:
- 50 minutes of lecture material (presented live, also recorded)
- 20 minutes of code demonstrations and exercises for you to try, with small-group "breakout" Zoom sessions available, attended by other class participants, and Teaching Assistants. Please help each other out!
- 10 minute discussion of exercises, where the instructors will present possible solutions and answer questions (also recorded)
Please join the module's Slack channel, where you can ask questions and see real-time updates from the instructors and TAs.
Zoom Room for all sessions
| Wednesday, July 20th | |||
|---|---|---|---|
| Time | Topic | Lecture | Exercises/Discussion |
| 11:30am-12:50pm | 0/1. Introductions, motivation for Bayes | Slides0 [.pdf] Slides [.pdf], Zoom Part1 Zoom Part2 | Exercises, Key [.pdf] Zoom |
| 1:10pm-2:30pm | 2. Binomial sampling, part 1 | Slides [.pdf], Zoom | Demo and exercises [.Rmd, .pdf], Key [.pdf] |
| Thursday, July 21st | |||
| Time | Topic | Lecture | Exercises/Discussion |
| 8:00am-9:20am | 3. Binomial sampling, part 2 | Slides [.pdf], Zoom | Demo and exercises [.Rmd, .pdf], Key [.pdf] |
| 9:40am-11:00am | 4. Multinomial Samples | Slides [.pdf], Zoom | Demo and exercises [.Rmd, .pdf], Key [.pdf] |
| 11:30am-12:50pm | 5. Linear models | Slides [.pdf], Zoom | Exercises Script from demo [.R] , Key [.pdf], Zoom |
| 1:10pm-2:30pm | 6. Model selection and averaging | Slides [.pdf], Code [.R], Zoom | Exercises Key [.pdf], Zoom |
| Friday, July 22nd | |||
| Time | Topic | Lecture | Exercises/Discussion |
| 8:00am-9:20am | 7. Generalized Linear Models | Slides [.pdf], prostmat.csv, prostz.txt, Zoom | Demo and exercises [.Rmd, .pdf], Key [.pdf] |
| 9:40am-11:00am | 8. Meta-analysis | Slides [.pdf], Zoom | Exercises Script file [.R] Key [.pdf], Zoom |
| 11:30am-12:50pm | 9. Testing and Multiple Testing | Slides [.pdf], prostmat.csv, prostz.txt, Zoom | Demo [.Rmd, .pdf] (no exercises for this session), |
| 1:10pm-2:30pm | 10. Software examples | Slides [.pdf], Zoom | See demo resources below |
Resources for Session 10: most of the examples run the HWE example - each example is self-contained
- WinBUGS example - requires installing WinBUGS.
- R2WinBUGS and JAGS example - requires installing R and its R2WinBUGS package. For the JAGS part you will also need to install JAGS itself and the rjags package
- Stan example - requires installing R. Windows users will also need Rtools, Mac users may need the toolchain and corresponding tools
- INLA examples - requires installing R. To get the INLA package for R, follow the non-standard procedure here
- Examples with DIC/WAIC, using the FMS data [.txt] from Andrea Foulkes' book
Comments forms and attendance certificates are available here - requires SISG account.
- ASAgene.txt: Data for Session 2 and 3
- diagen_bma: Data and posterior simulations for Session 6 - load into an R session with load()
- yX_FTO: Copy of the FTO data, for Session 6 - load into an R session with load()
- The R site, which includes the Comprehensive R Archive Network (CRAN) of downloads and packages
- A reference card of common R commands (and a slightly longer reference card)
- A First Course in Bayesian Statistical Methods (Hoff, 2009) - available free with UW login
- Bayesian and Frequentist Regression Methods (Wakefield, 2013) - available from with UW login
- Foulkes, Applied Statistical Genetics with R For Population-based Association Studies, 2009; this book covers a lot of the material we'll discuss, although seldom from a Bayesian point of view.
Last modified: 7/17/2021