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Statistics is the branch of applied mathematics concerned with the collection and interpretation of quantitative data and the use of probability theory to estimate population parameters. Along with computer science, statistics is at the center of “Data Science” – a discipline that has seen tremendous growth in the recent years with “Data Scientist” being voted the most satisfying job two years (2016, 2017) in a row in the United States.  Statistical studies are the basis of newspaper headlines every day, whether it be statistical indicators of the health of the economy, a study of the effectiveness of mammograms, or predictors of climate change and the trend of the financial market. For modern trends in statistics, see the New York Times front page story whose headline read “For Today's Graduate, One Word: Statistics”.   Go to NY Times statistics article.

The Stony Brook Department of Applied Mathematics and Statistics has a program of graduate training and research in Statistics, offering M.S. and Ph.D. degrees. Unlike most other graduate programs in statistics, the emphasis is on applied statistics and data science. In strong and weak economic times, there has always been a strong demand for our applied statistics M.S. and Ph.D. graduates locally including (1) New York City banking and investment companies, (2) New York area biomedical research centers, (3) insurance companies in Connecticut, (4) drug companies in northern New Jersey (the world's leading center for pharmaceutical research) as well as Pennsylvania. Our graduates also find strong job market globally in leading companies such as, Facebook, Google, Bank of America, Bloomberg, Goldman Sachs, JP Morgan, Amgen, FDA, Pfizer, Roche, etc. as data scientists, financial analysts/risk managers and biostatistics managers.

Our statistics faculty specializes in biostatistics and financial statistics. Our studies include examining the genetic and epigenetic basis of various diseases, and the analyses of financial market such as change points in financial time series, risk management for high frequency finance, as well as statistical models for the stress test mandated for major financial institutions. A unique line of study in our program is data science, also commonly referred to as big data. Related courses include AMS 595 (fundamentals of computing), AMS 530 (parallel computing) and AMS 598 (big data analysis). For more information about our research, see Statistics projects.

The standard professional degree for statisticians working in business and biomedical research is the M.S. degree. The department offers a 30-credit M.S. degree, with no thesis, that prepares students for such non-academic careers. All statistics M.S. students must complete an internship as a statistical consultant on some research project. The department also offers a Ph.D. degree which starts off with the same courses as the M.S. degree. For more details about requirements for the Ph.D., please see   Ph.D. Requirements.

Required Courses for M.S. Degree in Statistics Track

  • AMS 507 Introduction to Probability
  • AMS 510 Analytical Methods for Applied Mathematics and Statistics
  • AMS 570 Mathematical Statistics I
  • AMS 571 Mathematical Statistics II (required for PhD only)
  • AMS 572 Data Analysis
  • AMS 573 Design and Analysis of Categorical Data
  • AMS 578 Regression
  • AMS 582 Design of Experiments
  • AMS 597 Statistical Computing

plus two electives chosen from other graduate courses in the department or (with an advisor's approval) graduate statistics courses in other departments. The following is a list of some popular (and important) elective choices:

  • AMS 595 Fundamentals of Computing
  • AMS 586 Time Series   (*Receiving grades of B- or better in both AMS578 and AMS586 – is considered as the equivalence of the  VEE Applied Statistics  in the ASA Actuarial Exam.
  • AMS 598 Big Data Analysis
  • AMS 550 Stochastic Models 

Given that the track of Statistics is highly correlated with the track of Quantitative Finance (QF), interested students can choose to take selected courses in QF and obtain the  Advanced Certificate in Quantitative Finance . Please see following website for detailed information.

*** Please download the overview of the statistics track.***


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