Graduate Program
The Department of Statistics offers M.S. and Ph.D. degrees in Statistics.
Important Decisions and Regulations
Course Equivalency
- A course proposed as equivalent to a departmental must course must be at least 90% compatible in content with that must course. This rule applies to all undergraduate and graduate programs of the Department and to all equivalency requests submitted after 4 August 2026. (Departmental Academic Board decision, 4 August 2026)
Discontinued Courses
- Students who failed any of the courses listed in the table below, which were taken before the 2022–2023 Fall Semester and are no longer offered, must take the corresponding courses specified in the table instead.
→ Discontinued courses and their replacements
M.S. Degree in Statistics
Requires seven courses with at least 21 credit hours.
The curriculum consists of compulsory courses, departmental elective courses and non-departmental elective courses.
Compulsory courses are theoretical statistics courses and aim to give students a sound understanding of the theoretical basis of statistics.
Departmental elective courses aim to help students develop skills in statistical modeling and computational methods applied in areas such as economics, finance, marketing, sociology, psychology, genetics and medicine.
The degree requires conducting research and writing a thesis. A thesis is usually one of the following: methodological, computational, empirical or theoretical. In a typical methodological M.S. thesis, the student compares and evaluates different available statistical models and estimation methods through a simulation study. In a computational M.S. thesis, the emphasis is on computational statistical methods. In an empirical M.S. thesis, a novel data set is central to the thesis, and appropriate existing statistical methods are used for the analysis.
Ph.D. Degree in Statistics
Our Ph.D. program is designed to prepare students for academic careers and for industrial and government positions that involve consulting and research in new statistical methods.
Requires nine courses with at least 29 credit hours.
The curriculum consists of compulsory courses and other departmental courses.
Compulsory courses aim to give students a thorough grounding in probability theory and the theory of statistical inference.
Other courses towards this degree are designed to give students an in-depth understanding of methodologies related to different types of data, such as data obtained from designed experiments and, more broadly, multivariate data.
The degree requires conducting research and writing a thesis. A qualified Ph.D. thesis is based on research in a previously unexplored area. The research may be motivated by a novel or interesting existing data set for which there is no computationally efficient modeling approach that also provides estimators with the desired statistical properties.