2025 Summer of Bayes Stats Workshop main page

What: Five-week Bayesian generalized linear mixed models workshop series
When: Thursdays from July 31 through August 28, 2025, 2:00-5:00 PM Eastern time (1:00-4:00 Central)
Who: ARS researchers in the Southeast Area
Where: Broadcasting live from Raleigh, North Carolina via MS Teams

Quick links

Pre-workshop instructions

You have two options for following along with the code in the workshop.

Option 1 - SCINet: I have created a shared project space on the Ceres computing cluster run by USDA ARS SCINet. You can run the R code on RStudio Server using Ceres OnDemand without installing anything on your own computer. You will need to register for a SCINet account if you do not already have one, which you can do even if you’re not a USDA employee as long as you have someone in ARS act as your sponsor. Important - this may take a week or two, so please start the process well before the workshop! Then provide Quentin with your username and he will add you to the shared project space. You’ll get further instructions about how to access the shared space with the example data and pre-installed R packages and Bayesian software Stan. During the workshop, you will create RStudio Server sessions on Ceres OnDemand and run code from there.

Option 2 - Local computer: Install R, RStudio, all necessary R packages, and CmdStan on your own computer. We will not have time during the workshop to troubleshoot any installation issues that may arise. But you may find it more convenient in the long term to have access to all the software to fit models to your own data locally. Instructions on how to install R, RStudio, R packages, and Stan on your own computer are here.

Schedule and course materials

Virtual office hours

Before the workshop starts, we’ll hold multiple “virtual office hours” where people can stop by and get help either with getting access to SCINet, or with installing the needed software on their own machines. Please take advantage of the office hours to do pre-workshop troubleshooting. That way, we can devote the workshop time slots to learning about stats instead of getting frustrated about software!

Date and time TBA

Workshops

Each day, we will start at 2:00 PM Eastern/1:00 PM Central and go until 5:00 PM Eastern/4:00 PM Central, with a couple of 10-minute breaks included.

Below are the course materials for each week, including the full-text version of the lesson, the slides I’ll be teaching from, and the worksheet.

Date	Lesson text	Lesson slides	Code worksheet	Answers to Exercises
Week 1: Thursday, July 31	Lesson 1: Introduction to Bayes	Slides	Worksheet / Worksheet with blanks filled in	Answers
Week 2: Thursday, August 7	Lesson 2: Bayesian GLMMs	Slides	Worksheet / Worksheet with blanks filled in	Answers
Week 3: Thursday, August 14	Lesson 3: Bayesian space and time models	Slides	Worksheet / Worksheet with blanks filled in	Answers
Week 4: Thursday, August 21	Lesson 4: Beta, zero-inflated, and hurdle models	Slides	Worksheet / Worksheet with blanks filled in	Answers
Week 5: Thursday, August 28	Lesson 5: Ordinal and nonlinear models	Slides	Worksheet / Worksheet with blanks filled in	Answers

A note on the worksheets: The worksheets are fill-in-the-blank R scripts. During the workshop you’ll follow along by filling in the blanks in the code, following what I’m typing on my screen, and running it. If you fall behind or get stuck, I’ve also provided a version of the worksheet with the blanks filled in. Only use that as a last resort, because you really do learn better if you have to physically type out at least some of the code! The worksheets will be pre-loaded onto the shared project space on SCINet, but if you’re running the code on your own machine, you’ll need to download them from this page.

Self-study resources

If you are interested in learning more about Bayesian statistics, mixed models, or statistical programming in R, here are some learning resources that might be useful.

Instructor team

Quentin Read, instructor

Quentin has been the USDA ARS Southeast Area Statistician since 2021. He has a background in plant ecology and interdisciplinary socio-environmental research. His learning journey in R and Bayesian statistics began when he started grad school at the University of Tennessee in 2011 and continues to this day! He enjoys promoting R, Bayesian statistics, and open and reproducible science at USDA.

Grant Billings, teaching assistant

Grant Billings is a Postdoctoral Research Scholar at North Carolina State University, co-mentored by Dr. Jeffrey Dunne and Dr. Amanda Hulse-Kemp. His main interests are in the design and analysis of plant breeding field experiments, the application of statistics to genetics and genomics, and modeling biological systems through simulation. Grant collaborates directly with multiple University and USDA-ARS breeding programs, primarily focusing on peanut and cotton. Grant has been a daily R user since 2018, using traditional frequentist statistics and, more recently, Bayesian methods for making inferences from data.

Connection information

Participants will get MS Teams connection information via email. The workshop will be recorded and video will be posted on the SEA Statistics Workshops page on Axon+.

Post-workshop Survey

After the workshop, please fill out this anonymous feedback survey to help me improve future stats classes!

Page last updated 2025-06-26

SEAStats

Contents: