Program Requirements


  • Coursework
    • 36 credits
      • 24 graded STA; 6 graded/ungraded STA; 6 STA or non-STA
        • First-year MSS Core is a set of 8 recommended courses on Models & Methods, Theory, Computing and Practice
        • 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
  • Applied Statistics Experience
  • Progress Toward Completion
    • Each MSS student must complete the Progress Report Form and submit it to the DSG assistant by April 22.
  • Completion Exercise
    • Either Portfolio or Master's Thesis

First Year MSS Core

Fall Semester Spring Semester
STA 521 Modern Regression and Predictive Modeling 
STA 523 Programming for Statistical Science
STA 601 Bayesian and Modern Statistical Data Analysis

STA 531 Advanced Bayesian Inference and Stochastic Modeling
STA 561 Probabilistic Machine Learning

STA 581 ProSeminar: Becoming a Professional Statistician*
STA 663 Statistical Computing and Computation
STA 851 Statistical Consulting Workshop


Second Year Elective Courses

Electives offered typically in Fall Electives offered typically in Spring

STA 532 Theory of Statistical Inference
STA 613 Statistical Methods in Computational Biology
STA 621 Applied Stochastic Processes
STA 623 Statistical Decision Theory
STA 640 Causal Inference
STA 841 Generalized Linear Models
STA 944 Spatial Statistics

STA 321 Statistics of Surveys
STA 571 Advanced Machine Learning
STA 582 DataFest*
STA 641 Statistical Learning and Bayesian Nonparametrics
STA 642 Time Series and Dynamic Models
STA 643 Modern Design of Experiments

* 1 credit