M.A. in Statistics On-campus Program
The MA Program is a traditional program completed fully on campus. It may be completed on either a full-time or part-time basis. International students must complete the program on a full-time basis. Most courses have at least one evening section in order to accommodate students who work full-time. The full-time program is designed to be completed in three semesters – fall and spring semesters of Year 1 and fall semester of Year 2. Students may also opt to take summer courses. Part-time domestic students must take a minimum of two courses per semester and must complete the program within four years of the first semester of registration.
The MA program requires completion of at least two (2) 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 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 section). Students must confer with their adviser prior to any change in their course registration.
Required Core Courses
Students must complete four required core courses and six elective courses, with a total of ten minimum graded classes for the degree. Courses taken for Pass/Fail or R credit do not count as a core class or elective. All courses must be graded.
Of the six electives, at least three must be selected from courses offered by the Statistics Department. The other electives may be chosen from a list of approved courses, depending on the student’s area of interest. Students should review this information with their Faculty Adviser.
The four core courses:
- GR5203: Probability (a 1/2 semester course worth 3 points) immediately followed by…
- GR5204 Inference (a 1/2 semester course worth 3 points).
GR5203 and GR5204 are required to be taken in the first semester.
- GR5205: Linear Regression Models (3 points) – Required to be taken in the first semester.
Three core classes to be taken in the first semester.
- 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. All electives that count must be taken for a grade.
For a thorough grounding in data science, an incoming student is strongly advised to take W4300 (GR5206): Statistical Computing and Intro to Data Science (3 points) in the first semester. A partial list of approved electives may be found here.
Data Science Sequence
- In order to qualify to take GR5242 Advanced Machine Learning, one must have taken the prerequisite: GR5241 Statistical Machine Learning.
- In order to qualify to take GR5241 Statistical Machine Learning, one must complete the prerequisite: GR5206 Statistical Computing.
Data Science Sequence:
GR5206 – Statistical Computing (recommended to take fall semester 1 to qualify for subsequent courses in the sequence)
GR5241 – Statistical Machine Learning
GR5242 – Advanced Machine Learning