Multivariate Analysis for Community Ecology

Monique Rocca, Katie Renwick

Description:In this course, students will learn popular techniques for analyzing multivariate ecological data, with an emphasis on ordination and classification of multivariate data characteristic of community ecology. Students will gain a conceptual understanding of multivariate analyses and interpretation, and will practice implementing these techniques. By the end of the semester, students will be comfortable running community analyses within the R software package and have the skills necessary to perform a multivariate analysis that will stand up to peer review. We highly encourage students to register for 2 credits! In addition to participating in class and completing short weekly assignments, each student taking 2 credits will have the additional requirement of a journal-style manuscript (which may lead to a thesis chapter or a publication), due at the end of the semester. These students should have a dataset of their own with which to apply the techniques learned in the course. Students should have access to a laptop computer running R, and bring it to class each week.

Section: 4
Credits: 1
First Meeting: 8/25/2014
Meeting Times: Tuesdays between Sept 30-Nov 18 (8 weeks); 2-3:40 pm
Classroom: TBD
CRN: 60565
Cross Listed: Not cross listed
Enrollment Limit: 20
Background: Graduate statistics (511/512) and an ecology course in the student's discipline (plants, wildlife, etc.)
Course Text:
Instructor Contact Info:
      Monique Rocca 491-2112
      Katie Renwick