Raleigh December 2024 Stats Workshop main page

Course materials

Lesson 2 (Day 1)

Lesson 3 (Day 2)

Pre-workshop instructions

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

Option 1: I have created a project on Posit Cloud. You can run the R code on the cloud server without installing anything on your own computer. All you have to do is sign up for a Posit Cloud account (already paid for by the Area Office), join the project group, and create your own copy of the project template. Participants will receive an invitation link by email. Instructions for signing up for an account and joining the project are here.

The Posit Cloud server is only for demonstration and teaching purposes. It is not secure. NO GOVERNMENT-OWNED DATA MAY BE UPLOADED TO THIS SERVER.

Option 2: 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. However, if you want to analyze your own data with the methods you learn in the workshop, you will eventually need to install this software locally or run it on the SciNet cluster. Instructions on how to install R, RStudio, R packages, and Stan on your own computer are here.

Schedule

Times are Eastern Standard Time.

Day 1: Thursday, November 21, 2024

Time Activity Notes
9:00-10:15 AM Workshop Lesson 2. We will begin with brief introductions and make sure everyone can access the cloud server before we start on the lesson content. The lesson starts with a review of Bayes’ theorem and an exploration of prior distributions.
10:15-10:30 AM Break  
10:30-11:45 AM Workshop Lesson 2, continued (logistic GLM)
11:45 AM-12:00 PM Break  
12:00 PM-1:00 PM Workshop Lesson 2, continued (Gamma GLMM)
1:00 PM-2:00 PM Break  
2:00 PM-4:00 PM Virtual office hours / open Q&A time Optional

Day 2: Friday, November 22, 2024

Time Activity Notes
9:00-10:15 AM Workshop Lesson 3 (Bayesian models with space and time)
10:15-10:30 AM Break  
10:30-11:45 AM Workshop Lesson 3, continued (repeated measures models)
11:45 AM-12:00 PM Break  
12:00 PM-1:00 PM Workshop Lesson 3, continued (spatial additive mixed model)
1:00 PM-2:00 PM Break  
2:00 PM-4:00 PM Virtual office hours / open Q&A time Optional

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. He enjoys promoting R, Bayesian statistics, and open and reproducible science at USDA.



Grant Billings, teaching assistant

Grant Billings is a Bioinformatics Ph.D. candidate at North Carolina State University. 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 has been a daily R user since 2018, using traditional frequentist statistics and, more recently, Bayesian methods for making inferences from data.

Location

840 Oval Drive, Raleigh, NC
NCSU Plant Sciences Building
Room 3158 (conference room on third floor)

Virtual 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+.

Page last updated 2024-09-10