Program Requirements

All new students are required to attend MS BOOTCAMP WEEK (~one week before orientation)
Fall 2019 BOOTCAMP (AUGUST 11-19)

Requirements

  • Coursework
    • 36 credits
      • 24 graded STA; 6 graded/ungraded STA; 6 STA or non-STA**
        • First-year MSS Core is a set of 6 required 3-credit courses on models & methods, theory, computing and practice, plus a 1-credit pro-seminar. First-year students generally take additional courses from the recommended electives. A student having substantial prior courses in one or more of these may be permitted to substitute an alternative, more advanced course on approval of her/his advisor and the MSD. 
        • Second-year Core & Electives is a set of courses offering a diverse range of advanced and special topics including advanced courses specific to the STA MSS program.
    • Satisfactory progress on courses
      • 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.
  • Applied Statistics Experience (internship/research, industry day and alumni event participation)
  • Progress Toward Completion
    • Each MSS student must complete the Progress Report Form and submit it to the DGS assistant by April 22.
  • Completion Exercise
    • Either Portfolio or Master's Thesis (students planning on doing a thesis must begin early work on their research to meet the thesis deadline)

Required Core*

Fall Semester  Spring Semester 

STA 521 Predictive Modeling and Statistical Learning (first year)
STA 523 Programming for Statistical Science (first year)
STA 581 ProSeminar: Becoming a Professional Statistician*** (first year)
STA 601 Bayesian and Modern Statistical Data Analysis (first year)
STA 610 Multilevel and Hierarchical Models

STA 532 Theory of Statistical Inference (first year)
STA 663 Statistical Computing and Computation

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

Elective Courses****

Electives typically offered

STA 522 Study Design: Design of Surveys and Causal Studies (Spring)
STA 561 Probabilistic Machine Learning (Spring)
STA 571 Advanced Stochastic Models and Machine Learning (Fall)
STA 583 Internship Writing and Communication*** (Fall)
STA 613 Statistical Methods in Computational Biology (Spring)
STA 621 Applied Stochastic Processes (Fall)
STA 623 Statistical Decision Theory (Fall)
STA 640 Causal Inference (Fall)
STA 642 Time Series and Dynamic Models (Fall)
STA 650 Social Network Analysis (Spring)
STA 671 Advanced Machine Learning (Fall)
STA 841 Categorical Data (Spring)

*** 1 credit   ** 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; ****The Elective course offerings are recommendations that may change based on instructor availability. NOTE THAT NOT MORE THAN 6 CREDITS OF INDEPENDENT STUDY WILL COUNT TOWARDS THE MASTERS DEGREE.

MSS Focus Area/ Tracks

The Master's in Statistical Science (MSS) program provides guidance for students interested in particular statistics focus areas/ tracks: