This course will be primarily of interest to graduate students in wildlife research. The conceptual development and organization of multivariate statistical techniques and applications will be presented from a wildlife and ecology research perspective; however, the information will be applicable to any related discipline. This course is intended to provide the biologist with the following:

• An introduction to the use of multivariate statistics in ecological research;
• A conceptual organization of the various multivariate techniques, with respect to the types of research questions and data sets appropriate for each technique; and
• A "laypersons" working understanding of how to use and interpret the results of each technique, including, for each technique, a conceptual overview, list of assumptions, diagnostics for assessing the assumptions, sample size requirements, mechanics of performing the analysis using R, and how to interpret the statistical output of the analysis.

Beyond these overall content goals, this course is intended to:

• Provide students with an opportunity to work and learn in an interdisciplinary environment;
• Provide students with an opportunity to engage in active, student-directed learning.
• Provide students with an opportunity to refine their written and oral communication skills.

WHO SHOULD TAKE THIS COURSE: This course will be primarily of interest to graduate students in the Natural Resources Conservation Department and Organismal and Evolutionary Biology (OEB) program, although students from a variety of other departments may benefit as well. To accomplish the course goals and objectives, we will use a project-based learning approach. Students will work in teams on several group projects, and there will be a heavy emphasis on demonstrating mastery of the proper use and interpretation of multivariate techniques.

TEXT: McGarigal, K, S.A. Cushman, and S. Stafford. 2000. Multivariate Statistics for Wildlife and Ecology Research. Springer-Verlag, New York. Lecture notes by K. McGarigal; and assigned journal articles.

PREREQUISITES: Graduate standing in WFCON or OEB, or permission from instructor, and any upper-level statistics course covering analysis of variance and regression.