Program Requirements

Summary of Degree Requirements

Completion of the MS degree requires 30 credit hours of graduate coursework and a Master’s essay. At most six credit hours may be transferred from another accredited institution, or from within UNC-CH, for courses taken before admission to the MS program. This policy on transferring credits applies to courses taken in the STOR Department as well. Doctoral students in STOR may receive an MS degree upon the successful completion of their Preliminary Oral Examination. Requirements for the 5-year BS/MS degree program can be found here.

Coursework Timeline:
In keeping with University regulations, all work credited toward MS degrees, except transferred course work, must be completed within a period of five years from the first date of registration.

Detailed Degree Requirements

A. Core Courses

Students must take 5 out of the following 7 core courses:

Data Science (STOR 520 or BIOS 611)
Machine Learning (STOR 565) or Advanced Machine Learning (STOR 767)
Applied Statistics (STOR 664)
Optimization (STOR 512 or STOR 612 or STOR 614)
Stochastic Modeling (STOR 545* or STOR 641)
Theoretical Statistics (STOR 555 or STOR 654)
Probability (STOR 535 or STOR 536** or STOR 634)

B. Other Course Requirements

Students must take and pass 12 additional credit hours of STOR-related coursework either inside or outside the STOR Department; outside courses need to be approved by the STOR program’s Director of M.S. Studies.
Students must take at least 3 credit hours of STOR 992, MS essay. A maximum of 3 credit hours of 992 registration may be counted as part of the 30 credit hour minimum.
Students must pass all courses and have no more than nine credit hours of low pass, L.
Students must complete an MS essay. See details below.

C. Master’s Essay and Examination Committee

In addition to their coursework, MS students must also complete a Master’s Essay. In many cases the Master’s Essay contains the careful modeling and analysis of a data set using ideas and methods from statistics, optimization, or stochastic modeling, including a detailed description of the data set, and a review of the relevant literature. In other cases, a Master’s essay may present new theoretical results, computational methods, or simulations. Master’s essays are typically 20-30 pages in length.

The Master’s essay is completed under the supervision of a Faculty Advisor, who should be an adjunct or regular member of the STOR Department. With approval of the Graduate Studies Committee, a faculty member outside STOR may serve as a student’s Faculty Advisor.

In consultation with their Faculty Advisor, students should assemble a Master’s Committee consisting of the Faculty Advisor and one other UNC faculty member with interest or expertise in the student’s essay topic. With approval, individuals outside UNC can serve as second committee members. Satisfactory completion of the Master’s Essay is based in part on an oral presentation and defense of the essay before the student’s Master’s Committee. Presentations are typically 40-60 minutes in length and are usually closed to the public.

Master’s students have the option of completing their Master essay and presentation as part of the consulting course, STOR 765. In this case the written report of the final consulting project, including the description of the project and associated data set, methods of analysis, results, and conclusion, will constitute the Master’s essay, the instructor of the course and the client, or another appropriate faculty member, will constitute the Master’s Committee, and the in-class presentation of the report, with Committee members present, will constitute the essay defense.

Suggested Course Sequences

Students seeking broad training in Data Science and Analytics

Year 1 Fall : STOR 520, STOR 557, STOR 536**
Year 1 Spring: STOR 556, STOR 565, STOR 572
Year 2 Fall: STOR 664, Capstone***, and Elective
Year 2 Spring: STOR 665, Capstone***, and Elective

Students wishing to concentrate in Analytics for Decision-Making

Year 1 Fall: STOR 512, STOR 520, STOR 536**
Year 1 Spring: STOR 545*, STOR 572, and either STOR 515 or STOR 565
Year 2 Fall: Capstone*** and Electives
Year 2 Spring: Capstone*** and Electives

Students wishing to prepare for future PhD study

Year 1 Fall: STOR 555, STOR 536**, STOR 664
Year 1 Spring: STOR 512, STOR 545*, STOR 665
Year 2 Fall/Spring: Two Core STOR PhD Course Sequences + 1 Elective/Semester
- Optimization: STOR 612/614
- Probability: STOR 634/635
- Stochastic Models: STOR 641/642
- Statistical Theory: STOR 654/655

*: In Spring 2025 only, this course is offered as STOR 590 with title “Stochastic Modeling & Decision Analytics.”
**: In Fall 2024 only, this course is offered as STOR 590 with title “Advanced Methods of Probability.”
***: Capstone is only applicable for students who began the program in Fall 2024 or later.