Statistics

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” has been ranked as #8 in 100 Best Jobs by the US News & World Report. 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 Amazon.com, 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, financial statistics, and statistical learning (also referred to as machine learning). In recent years, to strengthen our education and research in AI and data science, we have also recruited several faculty members in related areas as can be seen from the Stat Track Overview  of the statistics track. 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 machine learning and AI methodologies and applications. These culminate in a unique line of study in our program -- Data Science. Related courses include AMS 595  (Fundamentals of Computing), AMS 530  (Parallel Computing), AMS 580  (Statistical Learning), and AMS 598  (Big Data Analysis), AMS 521 (Data Management), AMS 563 (Medical Image Analysis), as well as a set of modern machine learning and AI courses AMS 691 (including deep learning, reinforcement learning and natural language processing).

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. Furthermore, many of our master students continue to pursue their doctoral degrees in statistics and data science. The department also offers a Ph.D. degree that 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 (Fall)
AMS 510 Analytical Methods for Applied Mathematics and Statistics (Fall)
AMS 550 Stochastic Models (Spring *** only required for PhD students ***)
AMS 570 Mathematical Statistics I (Spring)
AMS 572 Data Analysis (Fall)
AMS 573 Design and Analysis of Categorical Data (Spring)
 Theory (Spring)
AMS 580 Statistical Learning (Spring) orAMS 586 Time Series Analysis (Fall)
AMS 597 Statistical Computing(Spring)

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 (Fall)
AMS 511 Foundation of Quantitative Finance (Fall)
AMS 516 Statistical Methods in Finance (Fall)
AMS 520 Machine Learning in Quantitative Finance (Fall)
AMS 521 Data Management(Spring) 
AMS 530 Principles in Parallel Computing(Fall) 
AMS 562 Introduction to Scientific Programming in C++(Fall) 
AMS 563 Medical Image Analysis(Spring) 
AMS 598 Big Data Analysis (Fall)
AMS 560 Big Data Systems(Fall)
AMS 580 Statistical Learning (Spring, if not chosen as a core course)
AMS 586 Time Series Analysis  (Fall, if not chosen as a core course)
AMS 550 Stochastic Models (Spring)

• Please also note new machine learning courses (various sections of AMS 691) available for Fall at the end of this document, and also at the AMS 691 website.
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  Typically, each student should take 3~4 courses (9~12 -credits) per semester.
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  Please refer to the University academic calendar for key dates and schedules.
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  Please refer to the AMS Department Graduate Course Schedule for all courses offered each semester.

Advanced Graduate Certificates (AGC)

The department also offers three advanced graduate certificates – and our students can apply and acquire 1 or more of these certificates to further strengthen and broaden your background. You can download the Stat Track Overview  and study these certificates in details.

(1) AGC in Data & Computational Science

Through IACS, we have a 17-credit Graduate Certificate in Data and Computational Science available to both AMS MS and PhD students. Please download the Stat Track Overview  for details about this and other two advanced graduate certificates available to our graduate students.  

(2) AGC in Quantitative Finance (QF)

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 15-credit Advanced Certificate in Quantitative Finance. Please see the following website for detailed introduction of this and our QF program in general.

(3) AGC in Operations Research (OR)

The department also has an 18-credit AGC on OR through the School of Professional development (SPD). Please note that unlike the Data Science and the QF certificates which are offered through the SBU Graduate School, this OR certificate is offered through the SBU SPD and thus the application paperwork is different from the other two. Please refer to the detailed guidelines provided here: Stat Track Overview  

 
*** Please download the Stat Track Overview of the statistics track. It includes course selection guidelines, graduate certificates introduction, and doctoral qualifying exam information. A must-read for all Statistics majors. ***