School of Humanities and Sciences
For students interested in the theory of statistics and/or probability, or for students who wish to apply statistical and probabilistic methods to a substantive area.
What You'll Study
The requirements for a degree in Statistics are flexible, depending on the needs and interests of the students. Some students may be interested in the theory of statistics and/or probability, whereas other students may wish to apply statistical and probabilistic methods to a substantive area. The department has long recognized the relation of statistical theory to applications. It has fostered this by encouraging a liaison with other departments in the form of joint and courtesy faculty appointments. In addition to courses for Statistics students, the department offers a number of service courses designed for students in other departments. These tend to emphasize the application of statistical techniques rather than their theoretical development.
Students wishing to build a concentration in probability and statistics are encouraged to consider declaring a major in Mathematical and Computational Science. This interdepartmental program is administered in the Department of Statistics and provides a core training in computing, mathematics, operations research and statistics, with opportunities for further elective work and specialization.
The undergraduate minor in Statistics is designed to complement major degree programs primarily in the social and natural sciences. Students with an undergraduate Statistics minor should find broadened possibilities for employment. The Statistics minor provides valued preparation for professional degree studies in postgraduate academic programs.
The Data Science minor has been designed for majors in the humanities and social sciences who want to gain practical know-how of statistical data analytic methods as it relates to their field of interest. The minor will provide students with the knowledge of exploratory and confirmatory data analyses of diverse data types (e.g. text, numbers, images, graphs, trees, binary input); strengthen social research by teaching students how to correctly apply data analysis tools and the techniques of data visualization to convey their conclusions. No previous programming or statistical background is assumed.