MAR 536: Biological Statistics II - spring

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.

Class 12126

Section 01 · Lecture · 4.00 units

Enrolling
Seats
25
Days
Wednesday
Time
11:00 AM - 12:30 PM ET
Instructor
Gavin Fay
Location
SMASTE-247
Instruction mode
In Person
Section type
Enrollment Section

Class 12126

Section 01 · Lecture · 4.00 units

Enrolling
Seats
25
Days
Tuesday Thursday
Time
2:00 PM - 3:15 PM ET
Instructor
Gavin Fay
Location
SMASTE-247
Instruction mode
In Person
Section type
Enrollment Section