The 36-unit program, designed primarily for part-time study, covers essential elements of statistical studies with courses in probability, statistical computation and model building, experimental design, survival analysis, Bayesian statistics, and stochastic processes.

Additionally, these courses, along with a required thesis practicum, provide a foundation for further doctoral-level study in mathematics and statistics, or in other academic disciplines such as anthropology, biology, economics, political science, and psychology.

In addition to providing a solid theoretical foundation, the program also offers applied value, providing tools, strategies, and technical skills in areas such as predictive analytics and big data to help professionals in many fields analyze large volumes of data, make reliable and productive business decisions, and use technology efficiently.

The program offers flexibility and a wide range of elective and applied courses that emphasize statistical analysis in mathematics, computer science, engineering, clinical investigation, biostatistics, economics, and business. Students may choose from a broad-based pool of elective courses across disciplines, or they may organize elective course work and design the required thesis practicum in one of the optional tracks that correspond to strong industry demand for statisticians: Biology and Health; Business and Finance; and Engineering and Materials.