Graduate Fellows Program
The SSC Graduate Fellows Program is a one semester appointment that provides guided experience in statistical consulting and dataset analysis. Students will learn how to consult on applied problems in a variety of different disciplines and will gain considerable experience in all aspects of the consulting role. Students may concentrate on either statistical or mathematical consulting.
M.S. in Statistics
The Master's of Science in Statistics is 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.Graduate Portfolio in Applied Statistical Modeling
The Graduate Portfolio Program offers 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.
Graduate Portfolio in Scientific Computation
The Graduate Portfolio 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.
Consulting Services
All students, faculty, and staff are eligible for up to one hour of free consulting each week. Tutorials and answers to FAQs are also available from the Consulting page.
Courses
Graduate level courses are offered throughout the year under the course code SSC. Short software courses (not for credit, typically three hours in length) are also offered periodically.
Summer Statistics Institute
The Summer Statistics Institute is held each year during the break between spring and summer semesters. Institute courses cover a variety of levels ranging from introductory statistics, to software-specific courses, to advanced topics such as Hierarchical Linear Modeling and Factor Analysis.