Where: Raleigh, NC (NCSU Plant Sciences Building, 840 Oval Drive Room 3152).
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.
Times are Eastern Standard Time. The workshop will be held on Friday, December 8, 2023.
|We will begin with brief introductions and make sure everyone can access the cloud server before we start on the content. We will start with some conceptual background: what is Bayes and what are the pros and cons of the Bayesian statistical approach?
|Hands-on experience fitting Bayesian mixed models to a simple dataset
|11:45 AM-12:00 PM
|12:00 PM-1:00 PM
|More hands-on experience with Bayesian mixed models
|1:00 PM-2:00 PM
|2:00 PM-4:00 PM
|Virtual office hours / open Q&A time
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.
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. student 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.
840 Oval Drive, Raleigh, NC
NCSU Plant Sciences Building
Room 3152 (conference room on third floor)
Virtual participants will get Zoom 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 2023-10-30