Time Schedule:
John R. Skalski
FISH 557
Seattle Campus
Statistical analysis of population data; design and analysis of mark-recapture experiments on natural populations; laboratory work on computers. Recommended: probability theory;Q SCI 292; Q SCI 483.
Class description
The first principles of demographic parameter estimation from a probabilistic and statistical perspective using data from fish and wildlife sampling, mark-recapture, and line-transect methods. Common methods to estimate abundance, density, survival, and recruitment will be covered.
Student learning goals
Basic probabilities distributions used to describe demographic data
How to construct likelihood models and derive maximum likelihood estimators
Common demographic models used in fish and wildlife science to estimate abundance, survival, and recruitment parameters
Ability to perform sample size calculations, determine model assumptions, and read quantitative literature
General method of instruction
Two 2-hour lectures per week, weekly assignments, help sessions as needed
Recommended preparation
Working knowledge of calculus essential.
Class assignments and grading
Weekly assignments will include constructing regression or likelihood models, derivation of parameter estimates and associated variances, analysis of demographic data, and sample size calculations.
Grade based on total numerical score from nine weekly homework assignments (450 points) and take-home final (150 points).
