As a student in the applied statistics and analytics program, you'll work alongside faculty members with expertise in actuarial and risk analysis, Bayesian techniques and applications, data mining, and more. This two-year program is designed for students interested in a career that requires advanced knowledge and skills in statistics and data analytics. In the age of big data, strong analytical skills and abilities to manage and interpret big data are in high demand in virtually every discipline. The applied statistics and analytics program will give you the skills and expertise to excel in any field.
Research Opportunities and Assistantships
Most of the courses require a semester-long research project. Students are encouraged to exhibit their projects at the annual poster presentation. Outstanding projects are recommended for international project competitions organized by
SAS Inc. In previous years, several student projects have won the competitions.
The department offers graduate teaching assistantships to master's students. Teaching assistantships are determined by the graduate committee based on students' academic credentials and previous teaching performance.
Admission to the applied statistics and analytics program requires:
- a four-year undergraduate degree or equivalent from a college or university of recognized standing;
- a minimum undergraduate GPA of 3.0;
- a minimum of 12 semester hours of mathematics and/or statistics with an average GPA of 3.0 or higher which must include calculus II, linear algebra and one course in statistics or probability;
- general GRE scores; and
- for international students, a minimum TOEFL score of 550 PBT, 79 IBT, 6.5 IELTS, 53 PTE, 5 IB or 77 MELAB.
The deadline for admission and financial support is Feb. 15. Apply online at
The M.S. in Applied Statistics and Analytics requires a total of 30-36 credit hours of academic work, which includes six hours of prerequisite course work, 27 hours of course work, and three hours of industrial internship.
For More Information
Lisa DeMeyer, graduate coordinator
Pearce Hall 210
989-774-5595 Carl Lee
Director, Data Mining/Analytics Program
Pearce Hall 109