NR 913 (01) - Hierarchical Modeling in Ecology

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
Class Size:   20  
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
ISBN
978012378605 0
PUBLISHER
ELSEVIER
BAYESIAN MODELS (15)
by HOBBS
Recommended
ISBN
978069115928 7
PUBLISHER
INGRAM PUB
Find Books for NR 913 (01) - Hierarchical Modeling in Ecology at the UNH Bookstore.