Bayesian Statistics in Ecology (ONLINE)


Bayesian Statistics in Ecology (ONLINE)

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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: This is a 1-credit equivalent academic course (16 contact hrs + additional work) where you learn at your own pace over 3 months.

You have two options when enrolling in this course:

(1) Instructor support. Reach out to your instructor over a 1-month period to get help as you work through prerecorded lectures, problem sets, and your own personal work. You then have access to the course for an additional 2 months. Instructor support includes emailing your instructor, accessing live discussion threads, and scheduling one-on-one appointments (Zoom or phone) about course material, your research, datasets from work, etc. You MUST select this option if you want to take the course for academic credit at your home institution or you would like to work with an instructor on a dataset from school or work.

(2) No instructor support. Sign up anytime over a 3-month period and learn at your own pace as you work through prerecorded lectures and problem sets. Be aware that at any time during the first month, you may upgrade to receive Instructor support.


DATES: Begins January 2, 2023 (instructor support begins in March)

ESA & TWS continuing education credits included for free!