M.A. in Statistics Hybrid Online/On-campus Program

The Department of Statistics offers its M.A. program in a partially online format, offering students greater flexibility in completing the M.A. Degree.  The first semester (only) of the hybrid program is offered online.  The remaining courses are completed on campus, during which time the hybrid students are completely integrated into the resident program.  

  • The degree requirements and the actual diploma/M.A. Degree rewarded are identical for both the hybrid online/on-campus program and the regular on-campus program. 
  • International students must attend full time and register for all four online courses in the first semester.**
  • A part-time student must complete the program in no more than four years.  Before choosing the part-time option, review the fall course schedule to see if the times will work for you. Our online courses tend to run during early morning hours and in-person virtual attendance depends upon the course instructor. 

All online students must be present (online) for quizzes and exams. Hybrid students, by program design, are remote during the fall semester and may not be on campus. 

Required Core Courses

Students must complete four required core courses and six graded elective courses, with a total of ten minimum classes for the degree.  Of the six electives, at least three must be selected from 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 for the Hybrid Program:

(1) GR5203:  Probability (online half-semester course worth 3 points) immediately followed by…

(2) GR5204:  Inference (online half-semester course worth 3 points).

(3) GR5205:  Linear Regression Models (online full-semester course worth 3 points)

           ***GR5203, GR5204 and GR5205 are taken online in the first semester***

(4) 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 graded 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. 

For a thorough grounding in data science, an incoming student is strongly advised to take (GR5206): Statistical Computing and Intro to Data Science (3 points) in the first semester online.  A partial list of approved electives may be found here

Data Science Sequence

  • GR5206:  Statistical Computing (online full-semester course worth 3 points) – Full-time hybrid students are required to take this course online in their first semester.
  • GR5241:  Statistical Machine Learning (3 points) – prerequisite is GR5206.
  • GR5242:  Advanced Machine Learning (3 points) – prerequisite is GR5241.

Each course must be successfully completed before taking the next in the series. 

**If you are an international student currently in the US in F-1 status, please consult with ISSO.