Master’s Program Description

The MS program in Statistics, Analytics and Data Science (STANDS) offers students a rigorous program of training in the areas of statistics, optimization, stochastic modeling, and probability. The program is designed to be flexible enough to accommodate students with different technical backgrounds and subject matter interests, and it allows students to pursue a variety of coursework in theory, methodology, computation, and applications.

The MS program in Statistics, Analytics and Data Science, formally an MS degree in Statistics and Operations Research, can function as a stand-alone, terminal, degree for individuals seeking jobs in the private or public sector. However, it also provides a valuable complement to a number of Ph.D. programs in the natural and social sciences, enhancing the credentials of students in these programs seeking academic or industry jobs. In the past, students have completed MS degrees in STOR concurrently with a Ph.D. in areas such as Economics, Sociology, Psychology, Mathematics, and Physics. Terminal Master’s students, who seek employment immediately after completion of the degree, have readily found jobs in industry and government.

The Statistics, Analytics and Data Science MS program requires 30 credit hours of graduate coursework, and the completion of a Master’s Essay. Students can choose from a wide variety of courses within the STOR Department, as well as a limited number of courses from outside the Department.

Prerequisites

Applicants to the MS program should have a strong record of undergraduate coursework in statistics and mathematics. Statistics coursework should include an introductory course in statistics, STOR 155, an intermediate level course in inference and regression, similar to STOR 455, and a calculus- based probability course, similar to STOR 435.

Mathematical coursework should include single and multivariable calculus, as well as an intermediate or advanced level course in linear and matrix algebra. Students interested in theoretical statistics or probability should have prior coursework in advanced calculus or real analysis.