The course will meet the Analytic or Stats requirement for the SEAS MS degree, but not both. This course will consist of an overview of standard and innovative techniques in ecological data analysis and modeling. Topics will include: linear regression, mixed effects models (fixed and random effects), maximum likelihood, general linear models and general additive models, survival analysis, time series, spatial analysis and Bayesian and hierarchical Bayesian approaches.  

This course is designed for students to work on their own data, or simulated data, related to their research projects or scientific interests. While reviewing the major statistical methods used in ecology, students will work on their projects and will be presenting their work to the class along the semester, these presentations will consist on: initial exploratory data analysis, selection of statistical analysis or modeling approach, implementation, and results.