Course Description
Concepts and practices of Bayesian modeling for problem solving in natural resources management. Comparison to frequentist approaches, with Bayesian analogues presented. Demonstration of usefulness of Bayesian approach to analysis of complex study designs, with emphasis on plant, insect, fish, and wildlife populations.
Athena Title
Bayesian Models for Consrv Sci
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Course Objectives
The goals of the course are to instill a basic understanding of and appreciation for Bayesian principles for the solution of problems in natural resources science; to gain practical experience in constructing, evaluating, and interpreting models under the Bayesian framework; and to explore classes of models useful for conservation science. After completion of this course, students will be able to design and build models suitable for addressing problems in their own research, write and execute programming code to analyze these models, and generalize concepts sufficiently to address future applications in their careers.
Topical Outline
1. Foundations – philosophy, probability, Bayes’ Theorem, Bayesian and frequentist approaches, common distributions, conjugacy 2. Solutions – analytical and computational approaches, software 3. Diagnostics – convergence, model fit, model comparison 4. Application to problems familiar (e.g., t-test, ANOVA, regression) and not so familiar 5. Hierarchical models 6. Models for marked populations (animal, plant, human) 7. Models for unmarked populations 8. State-space models 9. Spatial models