The MA Program is a traditional on-campus program. It may be completed full-time or part-time. International students must complete the program on a full-time basis within three semesters only.
- Fall (Year One)
- Spring (Year One)
- Students may opt to take summer courses
- Fall (Year Two)
Part-time domestic students:
- Are required to take a minimum of two courses per semester and
- Complete a minimum of two RUs (Residence Units)
- Finish the program within four years of the first semester of registration.
There are evening and weekend courses/sections to accommodate students who work full-time.
MA Program Requirements
The MA program requires completion of two RUs (Residence Units) and a minimum of 30 points of graded courses. A typical course is worth three points, although some are worth four or more points.
Students must complete:
- Four required core courses and
- Six elective courses: Three must be statistics electives
This makes a total of ten minimum graded classes for the degree. Courses taken for Pass/Fail or R credit do not count for graduation.
Students must meet with with their assigned Faculty Adviser for approval of their study plan each semester prior to course registration. It is the responsibility of the student to meet with his or her adviser.
During the semester, students struggling with a course should contact their Faculty Adviser immediately (See Good Academic Standing). Students must confer with their adviser prior to any change in their course registration.
Required Core Courses
The four core courses:
- GR5203: Probability (3 points)
- GR5204: Inference (3 points)
- GR5205: Linear Regression Models (3 points)
Most students take these three core classes in the first semester. Students with a prior background in probability and inference should take the half-semester versions of Probability and Inference.
- GR5291 Advanced Data Analysis (3 points) – Required “Capstone Course” to be taken in the last semester of the program.
Please note: Core courses cannot be waived regardless of prior background.
In addition to the four core courses, students must also complete at least six electives approved by their Faculty Adviser. At least three electives must be selected from the Statistics Department, upon approval by the Faculty Adviser. Electives may be chosen based upon a student’s area of interest. In order to count for graduation, an elective must be taken for a grade. A partial list of approved electives may be found here.
Data Science Sequence
For a thorough grounding in data science that is specifically designed for the students in our Statistics MA Program, it is recommended to take this sequence:
- GR5206 Statistical Computing and Introduction to Data Science: Incoming students should take this in the first semester.
- GR5241 Statistical Machine Learning (prerequisite: GR5206)
- GR5242 Advanced Machine Learning (prerequisite: GR5241)