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.
As in the resident program, the M.A hybrid program requires completion of at least two (2) Residence Units and a minimum of 30 points. A typical course counts for 3 points, although some may count for 4 or more points. The online semester consists of the three core courses (see below) and one specific elective (Statistical Computing and Introduction to Data Science). During the online portion, students must connect via email with their adviser to ensure they are registered for the correct courses and Residence Units (RU’s). International students must complete the program on a full-time basis including the online semester.
Upon completing the online classes and after arriving on campus in the second semester, each student will review courses and electives leading to the M.A. degree with their assigned Faculty Adviser. Students must have their study plan approved each semester prior to registering for classes. It is the responsibility of the student to reach out to their adviser. Students struggling academically should contact their adviser immediately (See Good Academic Standing section). Students must confer with their adviser prior to any change in their course registration.
The degree requirement consists of four core courses and six elective courses with a total of 10 minimum classes for the degree. Of the six electives, at least three must be selected from the Statistics Department course options. 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.
Four Core Courses
GR5203, GR5204, and GR5205 are required to be taken in the first semester and are available online.
(1) GR5203: Probability (a 1/2 semester course worth 3 points) immediately followed by…
(2) GR5204: Inference (a 1/2 semester course worth 3 points).
(3) GR5205: Linear Regression Models (3 points).
(4) One Capstone Course taken in the last semester of the program. The Capstone Courses are not available online. Choose one only:
- GR5291: Advanced Data Analysis (3 points) OR
- GR5242: Advanced Machine Learning (3 points) – New. Please see “New Data Science Sequence” below.
Core courses may not be waived regardless of prior background.
New Data Science Sequence
There will be a new Capstone Course option introduced in Fall 2017: GR5242 Advanced Machine Learning (3 points).
- 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.
New Data Science Sequence:
GR5206 – Statistical Computing
GR5241 – Statistical Machine Learning
GR5242 – Advanced Machine Learning – Capstone Course
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.
**Strongly recommended for all students in the first semester and available online is GR5206: Statistical Computing and Intro to Data Science (3 points). This counts as one of the three Statistics electives and is a prerequisite for the prerequisite for the Data Sequence Capstone Course.
A partial list of approved electives may be found here.
The Part-time Option
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 AM hours and live attendance depends upon the course instructor. All online students must be present for quizzes and tests.