The MA Program may be completed full-time or part-time.  However, students in F-1 status must complete the program on a full-time basis, and they have a maximum of three semesters to complete the program. 

Full-Time schedule: 

  • Fall (Year One) – RU – required.
  • Spring (Year One) – RU – required.
  • Students may opt to take summer courses.
  • Fall (Year Two) – ER

Students who complete their requirements after two semesters are expected to graduate at that time, but MOST full-time students complete their coursework in three semesters.  It is recommended to stay for the entire three semesters to have sufficient time to assimilate all the material and have ample time to search for jobs or Ph.D. Programs after graduation.   

Part-Time students are required to: 

  • Take a minimum of one course per semester,
  • Complete a minimum of two RUs (Residence Units), and
  • 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 credits:  Ten or more courses with letter grades.  A typical course is worth three points. 

Students must complete:

  • Three required core courses
  • One capstone course
  • Six elective courses (18 credits total):  A minimum of 3 courses (9 credits total) from this group must be from the Statistics Department.*

Students must receive a letter grade in all courses needed to count for graduation.  Courses taken for Pass/Fail or R credit will not count for graduation. 

It is the responsibility of the student to reach out to the assigned Faculty Adviser for approval of the courses to count for graduation.  It is recommended that each student send the MA PROGRAM COURSE CHECKLIST to the Faculty Adviser each semester prior to course registration and update the adviser with changes later on. 

During the semester, students struggling academically should contact their Faculty Adviser immediately (See Good Academic Standing).

Required:  Three core courses plus one capstone course. 

REQUIRED:  3 CORE COURSES

  • GR5203: Probability (3 credits)
  • GR5204: Inference (3 credits)
  • GR5205: Linear Regression Models (3 credits)

Most full-time students take these three core classes in the first semester.  Most MA Students take the half-semester versions of Probability and Inference. 

REQUIRED:  CAPSTONE COURSE

  • GR5291 Advanced Data Analysis (3 credits) – To be taken in the second or last semester.
  • GR5242 Advanced Machine Learning (3 credits) – GR5241 is the prerequisite for this course*

In addition to the three core courses, one capstone course is required.  Students are welcome to take both capstone courses, if desired.   In that case, one would count as a capstone, the other as an approved elective. 

*Electives

In addition to the four required courses above, students must also complete the equivalent of six (3-credit) approved electives.  At least three (3-credit) electives must be selected from the Statistics Department. 

In order to count for graduation, an elective must be taken for a letter grade.  A partial list of approved electives may be found here.  Electives may be chosen based upon a student’s area of interest.

Mentored Research (GR 5398) and Statistical Fieldwork (GR 5399) may be combined in order to count toward the 30 credit minimum for graduation:   

  • Faculty Adviser approval is required.
  • Each course must be taken for a letter grade.   
  • Mentored Research (GR 5398) and Statistical Fieldwork (GR 5399) may be combined for a maximum of 3 credits. 
  • The same course may not be taken twice in one semester. 

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
    • It is recommended to take this in the first semester.
    • This course counts as a statistics elective. 
  • GR5241 Statistical Machine Learning (prerequisite:  GR5206) – This counts as a statistics elective.
  • GR5242 Advanced Machine Learning (prerequisite:  GR5241) – This counts as a Capstone Course. 
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