Graduate Ecological Models and Data

Catalog description

Recent advances in computational sciences have facilitated methods of making inferences from data, fundamentally changing how biologists approach statistics. Students will learn how methods were developed and apply them to ecological examples. Topics include general principles of working with discrete and continuous data, maximum likelihood and Bayesian estimation techniques, and implementation of mixed and mixture models.  Students address ecological questions using data from a variety of currently available resources, and generate professional level reports and manuscripts. Introductory coursework in statistics is expected.