Analysis and Modeling of Ecological Data

Department Numbers
Department 1: 
NRE
Number 1: 
549
Description: 

The course will meet the Analytic or Stats requirement, but not both, although for the Stats requirement you will first have to consult with the instructor.  This course will consist on an overview of standard and innovative techniques in ecological data analysis and modeling. Topics will include: linear regression, mixed effects models (fixed and random effects), maximum likelihood, general linear models and general additive models, survival analysis, time series, spatial analysis and Bayesian and hierarchical Bayesian approaches.  This course is designed for students to work on their own data, or simulated data, related to their research projects or scientific interests. While reviewing the major statistical methods used in ecology, students will work on their projects and will be presenting their work to the class along the semester, these presentations will consist on: initial exploratory data analysis, selection of statistical analysis or modeling approach, implementation, and results.

 

Credits

Minimum Credits: 
3
Maximum Credits: 
3
Graduate: 
Yes
Prerequisites: 
Students are expected to have a (undergrad) background in calculus, algebra, and statistics. Students will need their own laptops for the R and OpenBUGS lab

Terms Offered

Fall Semester: 
No
Winter Semester: 
Yes
Comments: 

This course is offered every other year.