Bayesian Statistics in Ecology (ONLINE)

Photo of an albatross flying in the sky

Date and Time:

Tuesday, September 6, 2022, 9:00am to Friday, September 30, 2022, 11:59pm

Registration Deadline:

Monday, September 5, 2022, 11:59pm


COURSE DESCRIPTION: Bayesian methods for analyzing data are now widely used in ecology and wildlife management. The Bayesian approach involves specifying the “prior” distribution, which represents the uncertainty about the model parameters before we collect the data, and the likelihood, which represents the plausibility of different parameters values based solely on the data. These are combined via Bayes’ Rule to obtain the “posterior” distribution for the parameters, which represents the uncertainty about the parameters after we have analyzed the data. Using the Bayesian approach gives you more flexibility in the type of models that you can fit, compared to the classical frequentist approach, as the model is typically specified in the same way that you would write it down mathematically. Once you have become familiar with fitting a Bayesian model in R, you will appreciate the extra flexibility and the more intuitive way in which the results can be presented.

PREREQUISITES: Experience with the basics of probability, statistical methods (estimation and model selection), and using R to fit statistical models.

FORMAT: Students will take the course at their own pace over a four-week period. The course is composed of pre-recorded lecture material and exercises using R. Student interaction and instructor feedback will be provided in the form of email, online discussion forums, and live Q & A. Each student will also have the opportunity in weeks 2 and 4 to meet with the instructor via one-on-one video consultation to discuss their individual project from school or work.


DATES: September 6–30, 2022

ESA & TWS continuing education credits included for free!


How to Register:

For more information/to register, please visit our registration page.

Course fee: $650 professional / $550 student

Contact Email:

Contact Name:

Jessica Kennelly