Jornada Environmental Data Science lesson and workshop site
Date and time: Wednesday June 29, 2022 at 1:00pm Mountain time
Location: Garcia Hall conference room at Jornada Experimental Range HQ
Instructors: Darren James and Greg Maurer
Welcome to our ecological statistics and models workshop for the 2022 Jornada Desert Ecology Short Course. This workshop is the first of what we hope will be a series of “JEDS” (formerly JEST) workshops, with the aim of teaching introductory and intermediate data analysis and statistics skills to Jornada researchers using hands-on programming in R. This is the first-ever JEDS workshop, so please be patient with us.
This workshop will teach elements of statistical inference with ecological data, building from relatively simple linear models up to the (potentially) more complex use of mixed models. Mixed models are an active area of research and development in the statistics community, and there are numerous pitfalls and briar patches in the mixed model landscape. We’ll discuss them and demonstrate the basics, but our goal is primarily to give you the confidence needed to start exploring these methods on your own (and perhaps prepare you for a future mixed model workshop).
The lessons we are teaching have been developed using R, and we are expecting learners to code along with us as we subset the data, fit models, and interpret results. Please follow the general setup instructions to be prepared with a working version of R and RStudio. We will download data directly from the EDI repository at the start of the workshop (see more info on the teaching datasets page).
In addition to the basic preparations above, you should:
tidyverse, car, emmeans, multcomp, multcompView, lme4, and lmerTest.If you have trouble preparing or need help please contact Greg (gmaurer@nmsu.edu).
We have one big lesson for the workshop, and we will touch on only a few sections of it. Please keep in mind that this is a draft.
Here are the slides for the workshop:
Please tell us how the workshop went in the post-workshop survey. We’ll use your anonymous feedback to improve future workshops and lessons.