MAR 536: Biological Statistics II

Generalized linear models, inference of parameters in non-linear models, and Bayesian statistics. The course is designed for advanced graduate students in ecology and fisheries who want to study statistical theories in GLM and parameter inference, to infer parameters using the state-of -the art language (ADMB, BUG, R), and to develop his/her own models. Most models used in ecology and fisheries management are non-linear, and often many parameters are involved. The existing models/toolbox software are useful in research and practical management, but researchers often have their own unique problem, which those existing models cannot be used for.

2023 Spring
Class#SctTypeSeatsUnits
12661 01 Lecture 15 4.00
Days Start End Location
MON TUE WED THU FRI SAT 10:30 AM EST 11:30 AM EST SMASTE-247
Instructor: Gavin Fay Class status:
Non-Enrollment Section
Class instruction mode: In Person
2023 Spring
Class#SctTypeSeatsUnits
12664 01L1 Laboratory 15 4.00
Days Start End Location
MON TUE WED THU FRI SAT 10:30 AM EST 12:00 PM EST SMASTE-247
Instructor: Gavin Fay Class status:
Enrollment Section
Class instruction mode: In Person