Course Homepage: (Past Pages: Fall 2001 )

Purpose: To provide intermediate graduate students in environmental science, ecology, associated disciplines, and in statistics with a course of study in data analytic methods for problems in the environmental sciences. To provide a foundation for application of environmetric models and methods in future scientific research and policy-driven investigations.

Current Textbook: Statistics for Environmental Biology and Toxicology, by W.W. Piegorsch and A.J. Bailer. London: Chapman & Hall, 1997.

 

Topics Covered	Time
Fitting Statistical Models: non-linear least squares, maximum likelihood	0.5 weeks
Nonlinear Environmetric Response Models: polynomial, threshold, and truncated models; dose-response models; data transformation	2 weeks
Generalized Linear Models: logistic regression, log-linear models, and other generalized linear models	2.5 weeks
Quantitative Risk Assessment: observed effect levels, median effective dose and other potency estimators, added risk, extra risk, low dose extrapolation	2 weeks
Combining Information: combining p-values, meta-analysis, effect size estimation, using historical control information	2 weeks
Inference for Temporal Data: harmonic regression, Fourier analysis, ARIMA models, trend tests	2 weeks
Inference for Spatial Data: auto-correlated data, variograms and semi-variograms, kriging	2 weeks

The above textbook and course outline should correspond to the most recent offering of the course by the Statistics Department. Please check the current course homepage or with the instructor for the course regulations, expectations, and operating procedures.  

Contact Faculty: Don Edwards
(Last Updated: July 11, 2008)