NRES 593

Credit: 4 hours.

Focuses on statistical methods used to analyze ecological data. Includes application of general and generalized linear models including use of several probability distributions such as normal, binomial, Poisson, and negative binomial. Course also focuses on mixed models and approaches for imposing structure onto the variance-covariance matrix to account for non-independence or heterogeneous variance. Emphasis throughout is on evaluating and presenting results using both traditional (p-value) and information-theoretic (AIC) approaches.

4 graduate hours. No professional credit. Prerequisite: At least one course in ecology, including basic concepts of population and community ecology, and at least one course in statistics, including basic concepts of sampling, hypothesis testing, and techniques such as t-tests, linear regression, and ANOVA (e.g., CPSC/NRES 440 or equivalent). Graduate standing or permission of instructor required.