Graduate level courses are offered throughout the year under the course code SDS. Short software courses (not for credit, typically three hours in length) are also offered periodically.
A four-year degree that focuses on training future researchers on the theory and methods of statistics. Major emphases are placed on probability models and modern computational statistical tools. Throughout the program, students are exposed to central ideas of both Bayesian and classical approaches to inference.
Offers a a cohesive course of study for graduate students seeking to enhance the statistical modeling component of their research and to prepare for successful careers upon graduation. Students must complete 12 semester hours of courses including an independent study and present their work at a semi-annual colloquium upon completion of the program.
Offers a cohesive course of study for graduate students seeking to apply scientific computation tools to their research. Students must complete 12 semester hours of courses including an independent study and present their work at a semi-annual colloquium upon completion of the program.
A two-year program offering a mix of theory and application. Students must complete 33 hours: six hours of classical statistics, six hours of mathematical statistics, nine hours in major electives, and nine hours in a minor electives plus a master's report.
