M.P.S. Degree

The Department of Mathematics and Statistics offers a degree program leading to a non-thesis Master of Probability and Statistics (M.P.S). This degree is designed to provide a suitable mix of theoretical and applied background for students interested in a career in statistics. The curriculum provides students with the necessary technical, analytical and interpretive skills required of professional statisticians while concentrating on education in the fundamentals of statistics and its interdisciplinary nature. M.P.S. students are required to complete a project that may involve statistical consulting, programming and/or data analysis.  

Degree Requirements:

The department requires all candidates for the Master of Probability and Statistics to complete a project that may involve statistical consulting, programming and/or data analysis and present it to the Masters Advisory Committee that consists of three members of the faculty.

Course Requirements:

A minimum of 30 credit hours are required for the Master's degree.  A student may transfer up to six semester hours of graduate level courses, earned with a grade of B or better from an institution approved for this purpose by the Graduate School.  The department may waive some of the course requirements for those students who have taken equivalent course work at another institution.  Students must successfully pass three hours of Project STAT 7980 and may count at most 3 additional hours of 69XX or 79XX course work toward the degree.

Required Courses:

STAT 7600 Statistical Theory I (3) pr. STAT 3600 
STAT 7610 Statistical Theory II (3) pr. STAT 7600 
STAT 7020 Regression Analysis (3) pr. STAT 7000 
STAT 7840 Multivariate Analysis (3) pr. STAT 7000

Elective Courses:

STAT or STAT/MATH courses number 6000 and above, or applied probability and statistics courses from outside the department with permission of the student's advisory committee.


STAT 7980, 3 credit hours, required of non-thesis students may involve statistical consulting, programming and/or data analysis. It is intended to give students the opportunity to apply their knowledge to real-world problems in a supervised setting.

Last updated: 08/28/2012