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Statistics is relentlessly interdisciplinary. Statistical tools and methodologies have applications in virtually every discipline across campus. The Department of Statistics and Data Sciences is a community engaged in research and education in statistics and scientific computation. SDS offers graduate and undergraduate students an extensive inventory of courses as well as academic degree programs.

 

Undergraduate

*Please note: SDS does not currently house an undergraduate degree program. CNS Students: To find out who your advisor is, CLICK HERE.
Undergraduate Courses
Undergraduate level courses are offered throughout the year under course code SDS. 

Undergraduate Certificate in Scientific Computation & Data Sciences
Provides students the opportunity to develop mathematical, statistical, and computer-based techniques to investigate complex systems.

Undergraduate Certificate in Applied Statistical Modeling
Provides students majoring in allied disciplines with opportunities for skill development in advanced statistical methods.

 

Graduate

Graduate Courses
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. 

PhD in Statistics
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.

Graduate Portfolio in Applied Statistical Modeling
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.

Graduate Portfolio in Scientific Computation
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.

MS in Statistics
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.