Ecology of Health and Disease (Biology 370)
Ecology of species interactions in changing environments and how they influence human and animal health. Starting in 2020 I now teach the course every fall semester. [Previously taught General Ecology, Bio 372]
- Here are the readings I wrote for the class. (You are welcome to use or adapt them.)
- Here are some interactive Shiny apps I created for the class
Herpetology (Biology 432)
An overview of the evolution, ecology, physiology, and other cool aspects of the biology of amphibians and reptiles. This class is taught every other spring semester, in even years.
Quantitative Methods & Statistics in Ecology (Biology 572)
As ecologists we’re used to the messy realities of nature. We think carefully about how to approach a problem, spend inordinate amounts of time researching methods and equipment, and then, when everything breaks, find creative work-arounds to make our experiments work somehow. Yet when it comes to analyzing our messy, complex data we seem to look for the quick way out—canned statistical packages that we don’t understand, tortured transformations to shoe-horn our data into a form that we can plug into a statistic we already know, or worst of all, ignoring lots of data because we don’t know what to do with it. Well not any more!
This graduate class has gone through many iterations, but now focuses on teaching Bayesian approaches to fitting models to data. We use Richard McElreath’s excellent book Statistical Rethinking as our guide.
The basics of presenting data (Vassar College URSI program, 2019)
A short introduction to how one should present one’s data to convey their message. The handout can be found here.
Modeling infectious disease (5th International Symposium on Ranaviruses, Townsville, Australia, 2019)
A very brief introduction to compartment models and how to use the R package
simecol to solve/run them. The handout can be found here.
Design of ranavirus surveillance studies and data analyses (3rd International Symposium on Ranaviruses, Gainesville, FL., 2015)
In this workshop taught with Matt Gray, students learned how to effectively design and analyze surveillance studies. Topics included linking study objectives to data collection, prevalence versus incidence, infection versus disease, sample size determination, and data analysis. The presentations and slides can be found here.
Surviving Survival Analyses (SICB 2012)
A brief introduction to survival analyses including Kaplan-Meier survival curves, Log-rank tests, Cox proportional hazards, and Parametric survival models, with code in R. The handouts and slides are in this zip file.