This is a 2-day course on the Information-Theoretic approach to statistical inference, presented by Dr. David R. Anderson, Emeritus Professor, Department of Fish, Wildlife, and Conservation Biology, Colorado State University, Fort Collins, Colorado.
This course will focus on the practical application of these new methods and are based on Kullback-Leibler information and Akaike's information criterion (AIC).
The material will follow Dr. Anderson's recent textbook:
Model Based Inference in the Life Sciences: A Primer on Evidence
(Anderson, D. R. 2008. Springer, New York, NY 184 pp.)
A copy of this book is included in the registration fee.
The course will stress science and science philosophy as much as "statistical methods." The focus is on quantification and qualification of formal evidence concerning alternative science hypotheses.
The course is not about how to derive models for various science hypotheses or how to estimate the unknown parameters in these models (e.g., least squares or maximum likelihood). The presentation will assume a working knowledge of these issues.
For more insights into what this course is about, please see Dr. Anderson's website.
The course will be held on the
Humboldt State University campus,
in Science B, room 135,
Saturday and Sunday, October 15 and 16, from 8 a.m. to 4 p.m. each day.