NR 913 (01) - Hierarchical Modeling in Ecology

Hierarchical Modeling Ecology

Durham   Life Sciences & Agriculture :: Natural Resources
Credits: 4.0
Term: Spring 2022 - Full Term (01/25/2022 - 05/09/2022)
Grade Mode: Letter Grading
Class Size:   18  
CRN: 57025
This course uses modern Bayesian statistical modeling approaches to analyze ecological data, with an emphasis on applied hierarchical models. These models will be used to examine ecological systems and related topics including: population and community dynamics, experimental design, spatial patterns, species abundance and diversity, community organization, metapopulations, and landscape processes. To be successful in the course students should have taken a course in statistics and have working knowledge of the R programming language. Pre-req: Statistics.
Department Approval Required. Contact Academic Department for permission then register through Webcat.
Instructors: STAFF

Times & Locations

Start Date End Date Days Time Location
1/25/2022 5/9/2022 MW 10:10am - 12:00pm JAMS 140