Hierarchical Modeling Ecology
Durham
Life Sciences & Agriculture :: Natural Resources
Credits: 4.0
Term: Spring 2024 - Full Term (01/23/2024 - 05/06/2024)
Grade Mode: Letter Grading
Term: Spring 2024 - Full Term (01/23/2024 - 05/06/2024)
Grade Mode: Letter Grading
Class Size:
20
CRN: 56699
CRN: 56699
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.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Rem Moll
Times & Locations
Start Date | End Date | Days | Time | Location | |
---|---|---|---|---|---|
1/23/2024 | 5/6/2024 | MW | 10:10am - 12:00pm | KING N129 | |
Final Exam | 5/15/2024 | 5/15/2024 | W | 10:30am - 12:30pm | KING N129 |
Booklist
Book | Details |
---|---|
INTRODUCTION TO WINBUGS F/ECOLOGISTS
(10)
by KERY Recommended
|
|
BAYESIAN MODELS
(15)
by HOBBS Recommended
|
|