(Same as Environment M235.) Seminar, three hours. Limited to graduate students. Requisites: undergraduate level calculus, linear algebra, and introductory statistics; scientific computing. Introduction to statistical approaches in environmental science, with focus on climate science. Topics include Bayesian modeling, hypothesis testing, regression, causality, multidimensional data analysis, time series modeling, and extreme value analysis. Draws upon relevant examples in scientific literature. S/U or letter grading.