MS Focus Areas/ Tracks

The Masters in Statistical Science program offers a general course selection guidance for students interested in specializing in particular statistical focus areas/ tracks. Note that these are just suggested recommendations and not formal requirements. 


PhD/ Research

Research/PhDSome of our MSS graduates move into post-MS PhD programs in statistics and allied disciplines. The MSS core and recommended courses define a firm basis for students on this track. Such students take several advanced MSS elective courses in year 2 and in consultation with their MSS advisors and the MSD, will customize choice of electives to match their intended PhD field. In addition, we strongly recommend that students aiming to apply to PhD programs develop the MSS thesis rather than the MS portfolio; the demonstration of research interests and achievement in a thesis is generally a strong positive in PhD applications. 

On course selection, students targeting a PhD in statistics programs benefit from electives covering more theoretical as well as advanced material in core areas of statistics (e.g., STA571, 640, 641, 642, 643, 841, 944). Some students with relevant pre-requisites and with permission of course instructors may take one or more STA PhD level course. One example is STA711 that provides theoretical background that some leading PhD programs regard as beneficial at the time of PhD application. In other cases, students may propose to substitute a core MSS course with a PhD level course such as STA732 in place of STA 532, or STA 831 in place of STA 531. In all such cases, the student will consult with their MSS advisor and MSD prior to requesting permission from the instructor of the advanced course; the decision whether or not to admit is that of the course instructor. Students without a background in mathematical analysis may also consider taking Math 531/532 (analysis sequence).

Some of our MSS graduates aim at PhD programs in related areas requiring and involving a major aspect of statistics.  In such cases, the MSS tracks linked to key areas provide guidance on course selection.  For example, students interested in PhD programs in economics/econometrics or business administration are recommended to consider electives highlighted in the Economics & Finance track. Similarly, students interested in PhD programs in biostatistics, biology and allied areas are recommended to consider electives highlighted in the Health Data Science track, while students interested in PhD studies in computer science and/or machine learning will typically emphasize electives noted in the Data Science & Analytics track.

Selected Universities/PhD Programs for Past MSS alumni :

  • Boston University
  • Duke University
  • Harvard University
  • University of North Carolina
  • University of Southern California
  • University of Washington

Data Science & Analytics 

Data Science & AnalyticsStudents interested in MS focus on Data Science and Analytics are recommended to take all of the MSS core first year courses, with a particular focus on those emphasizing modeling (STA521, STA531) and computation (STA523, STA663). It is also strongly recommended that students complete the machine learning sequence by taking STA561 (Probabilistic Machine Learning) and STA571 (Advanced Machine Learning).

In their second year, students should further specialize by taking applied modeling focused elective courses. In particular, STA522 (Experimental Design), STA623 (Statistical Decision Theory), and STA841 (Categorical Data Analysis) are all excellent options that should help students develop relevant knowledge and skills. Additionally, STA 851 (Statistical Consulting) provides an opportunity for students to engage with wide range of complex real world data. Finally, it is critical that students develop strong programming skills in a variety of different languages. The core courses provide an introduction to both R (STA523) and Python (STA663). Beyond this, students are encouraged to learn at least one compiled language (e.g. C or C++) as well as being familiar with SQL and at least one distributed computing platform (e.g. Spark). Courses offered by the computer science as well as the electrical and computer engineering department are particularly relevant for developing these skills. For example, ECE 551D (Programming, Data Structures, and Algorithms in C++) and CS516 (Database Systems) address these specific skills.

Selected Past Employers :

  • McKinsey & Company
  • Goldman Sachs
  • QuaEra Insights
  • Liberty Mutual
  • Google, Inc.
  • Tesla
  • Uber

Finance & Economics 

Finance & EconomicsThe MS track in finance and economics stresses the courses STA 521 and 531 that are critical core/foundations for students to develop skills and experience in the basic statistical methodologies relevant as they move into such areas. Students on these tracks are then advised to consider MS electives such as STA 642 (Time Series and Dynamic Models, linked to areas of modeling and forecasting especially in finance and business), STA 640 (Causal Inference, linked areas including comparative effectiveness research, observational studies, and others), and STA 623 (Statistical Decision Theory, linked to evaluation of decision problems).

Students may and will typically consider adding at least one, possibly two electives in other programs and departments, with and following detailed consultation with their MS advisor. There are several relevant graduate courses offered at Duke in the Fuqua School of Business and in the Department of Economics. Some students may elect an introductory or second-level course in econometrics (e.g., ECON 608D, Introduction to Econometrics; ECON 612, Time Series Econometrics; among others) and/or in finance (e.g., ECON 413, Forecasting Financial Markets; ECON 571, Financial Markets and Investments; BA 551: Empirical Asset Pricing; BA 553: Theoretical Asset Pricing, among others). 

Selected Past Employers :

  • Capital One
  • Wells Fargo
  • Visa
  • BlackRock
  • UBS, Warburg, LLC. 

Health Data Science

Health Data ScienceThe MS focus in Health Data Science stresses the courses STA 521, 523, 531, that are critical core/foundations for students to develop skills and experience in the basic statistical methodologies as well as computer programming relevant as they move into such areas. Students on this track are advised to consider taking MS electives including STA 640 (Causal Inference, linked to comparative effectiveness research, observational studies, and clinical trials), and STA 522 (Study Design: Design of Surveys and Causal Studies), linked to areas of surveys. 

Students may and will typically consider adding at least one, possibly two electives in other programs and departments, with detailed consultation with their MS advisor. There are several relevant graduate courses offered at Duke in the Department of Biostatistics and Bioinformatics, e.g., BIOSTAT 713 (Survival analysis), BIOSTAT 718 (Analysis of Correlated and Longitudinal Data), and BIOSTAT 710 (Statistical Genetics and Genetic Epidemiology).

Selected Past Employers :

  • ICON, plc
  • Abbvie, Inc.
  • Illumina
  • Biogen
  • Lean TaaS

Marketing Research & Business Analytics

Marketing Research & Business AnalyticsThe MS focus in Marketing and Business recommends that the students take core courses STA 521 (Predictive Modeling), STA531 (Advanced Stochastic Modeling), and STA 561 (Probabilistic Machine Learning) that expose them to the basic statistical methods relevant to these areas. Students on this track are advised to then choose elective courses related to the modeling and forecasting area including STA 640 (Causal Inference), STA 642 (Time Series and Dynamic Modeling), and STA 841 (Methods and Models for Categorical Data).

Other applied courses that expose students to the real world data include STA 851 (Statistical Consulting). Further, the students in this track may consider adding least one and possibly two electives in other programs and departments in consultation with their advisor. These may include relevant courses across various departments offered in the Fuqua School of Business, e.g., MARKETING 796E (Market Intelligence) or DECISION 611C (Decision Modeling) or in the Department of Economics, e.g., ECON 608D (Introduction to Econometrics). 

Selected Past Employers :

  • Carnival Cruiseline
  • Merkle
  • ComScore
  • Neustar
  • Panton, Inc.

Social Science & Policy

The MS focus in Social Sciences & Policy stresses the courses STA 521, 531, 523 that are critical core/foundations for students to develop skills and experience in the basic statistical methodologies as well as computer programming relevant as they move into such areas. Students on these tracks are then advised to consider taking MS electives including STA 522 (Design of Surveys and Causal Studies, linked to areas of survey design and analysis and observational studies), STA 640 (Casual Inference, linked to comparative effectiveness research and program evaluation), and STA 650 (Social Networks, linked to analysis of relational data, particularly in social sciences).

Students may and will typically consider adding at least one, possibly two electives in other programs and departments, with and following detailed consultation with their MS advisor. There are several relevant graduate courses offered in other programs at Duke, e.g.  SOCIOL 725, 726 (Demographic Methods) in the Department of Sociology.  

Selected Past Employers :

  • US EPA
  • Rand Corporation
  • Institute for Social Research, University of Michigan

There are many other potentially relevant courses at varying levels in terms of requirements for prior exposure in each of the above tracks. Each student must balance interests with ensuring the core knowledge and expertise from STA courses and discuss with her/his MS advisor and the program director about potentially relevant courses.