This course develops fundamental methodology to the analysis of multivariate data. Topics include the multivariate normal distributions, multivariate regression, multivariate analysis of variance (MANOVA), principal components analysis, factor analysis, and …
Course provides an introduction to Bayesian methods with an emphasis on modeling and applications. Topics include the elicitation of prior distributions, deriving posterior and predictive distributions and their moments, Bayesian …
This course develops skills in reading the statistical research literature and prepares the student for contributing to it. Each student completes a well written and properly formatted paper that would …
This course introduces fundamental concepts in the classical theory of statistical inference. Topics include sufficiency and related statistical principles, elementary decision theory, point estimation, hypothesis testing, likelihood-ratio tests, interval estimation, …
This course covers advanced theory and methodology in probability. It includes, but is not limited to, substantial, in-depth coverage of topics in stochastic processes. Context and additional topics vary by …
This course develops skills related to the practice of statistical consulting. It covers conceptual topics and provides experience with data analysis projects found in or resembling those in statistical practice. …
Advanced graduate seminar in current research topics. Offerings in each semester are determined by student and faculty research interests.
For doctoral research, taken before a dissertation director has been selected.
For doctoral research, taken under the supervision of a dissertation director.