Program Requirements

All new students are required to attend MS Boot Camp

The Statistics  and Computing Bootcamps take place in August, prior to the start of Fall courses. The Fall 2023 Bootcamp is scheduled for August 14th-August 18th, 2023.

This intensive boot camp will focus on preparing incoming students for the Fall courses. It will cover computing and other fundamental math and statistics topics such as linear algebra, probability, Bayesian statistics, and programming.  Our students, especially those who gave a break after their undergraduate studies, find the boot camp very useful. Boot camp is required of all incoming MSS students.



  • 36 credits: 24 graded STA; 6 graded/ungraded STA; 6 graded STA or non-STA
  • The MSS Core is a set of six required 3-credit courses on models & methods, theory, computing and practice, plus a 1-credit pro-seminar. A student with substantial prior coursework in one or more of these may be permitted to substitute an alternate, more advanced course with approval of their advisor and the Master's Director (MSD) prior to registration.
  • MSS Electives offer a diverse range of advanced and special topics, including advanced courses specific to the STA MSS program.
  • External Electives are graduate level courses related to a student’s track offered by other academic departments at Duke University. If students need to take more than 6 credits external to the department (and have it count toward the degree), they should get approval from the Master's Director (MSD) prior to registration.

Prerequisites: Some courses, including required first-year courses, have formal prerequisite courses. A student whose grade on a prerequisite course is lower than C+ may be required to undertake additional assignments to enroll in the required course, following discussion with the course instructor and the MSD.

Progress Toward Completion: Each first-year MSS student must complete the Progress Report Form and submit it to the Director of Graduate Studies Assistant (DGSA) by the last week of April.

Graduate School Requirements: All master’s students are required to complete four hours of RCR training during their orientation and an additional two hour RCR forum before graduation. Master’s students required to take English for International Students (EIS) courses must receive grades of “CR” (credit) for those courses to be certified to graduate.

Other Departmental Requirements:

  • Required department events (Alumni Day, Departmental Career Fair or Industry Day)
  • First-Year Progress Report
  • Exit interview and survey

Completion Exercise: Students must complete either a Capstone project, Portfolio of Work presentation or a Master's Thesis. Students planning on writing a thesis must begin early work on their research to meet the thesis deadline.

Required Core

The requirements are somewhat flexible depending on student background and interest. Any changes to the requirements must be approved by the Master's Director (MSD) prior to registration.  

First Year

STA 521L  Predictive Modeling and Statistical Learning (Fall)
STA 523L  Programming for Statistical Science (Fall)
STA 581    ProSeminar: Becoming a Professional Statistician (Fall)
STA 602L  Bayesian and Modern Statistical Data Analysis (Fall)
STA 532    Theory of Statistical Inference (Spring)
STA 663L  Statistical Computing and Computation (Spring)

Second Year

STA 610L   Multilevel and Hierarchical Models (Fall)

Elective Courses

The list of offered elective courses will vary each semester.

STA 522     Study Design: Design of Surveys and Causal Studies
STA 540L   Case Studies in Statistical and Data Science
STA 561D  Probabilistic Machine Learning
STA 571     Advanced Stochastic Models and Machine Learning
STA 583     Communicating Statistics
STA 613     Statistical Methods in Computational Biology
STA 621     Applied Stochastic Processes
STA 623     Statistical Decision Theory
STA 640     Causal Inference
STA 642     Time Series and Dynamic Models
STA 643     Modern Design of Experiments
STA 650L   Social Network Analysis
STA 671D  Advanced Machine Learning
STA 690     Special Topics in Statistics
STA 693     Research Independent Study*
STA 798     Capstone Project
STA 841     Categorical Data
STA 863     Advanced Statistical Computing
STA 995     Internship

* Note that no more than six credits of Independent Study will count towards the completion of the Master’s Degree.