The Ph.D. program prepares students for research careers in probability and statistics in academia and industry. The first year of the program is spent on foundational courses in theoretical statistics, applied statistics and probability. In the following years, students take advanced topics courses Students also take part in the Department's consulting service. Dissertation work typically begins in the second year. Students also have opportunities for teaching experience, and for taking part in a wide variety of projects involving applied probability or applications of statistics.
M.A. in Quantitative Methods in the Social Sciences
The department participates in the interdisciplinary M.A. program in Quantitative Methods in the Social Sciences. The QMSS program trains students to apply quantitative methods to social problems as they arise in business, government, and nonprofit organizations, and provides a strong foundation for those who go on to doctoral programs in the social sciences. It is designed for students with a background in social sciences or quantitative methods who are interested in deepening their analytical skills and broadening their knowledge of the social sciences.
M.S. in Actuarial Science
The Department of Statistics, in conjunction with the School of Continuing Education, is launching an MS program in Actuarial Science in the fall of 2006. The program curriculum includes courses in probability and statistics, economics, business, and actuarial science. Students also have opportunities to take electives in a variety of areas, including advanced data analysis, financial engineering and mathematical finance, econometrics, and stochastic models. Completion of the program will provide a solid foundation in the theory and methods needed for advancement in the insurance industry. The curriculum includes courses to satisfy the VEE requirements and provides preparation for the first four SOA and CAS exams. Individualized study plans allow for both full-time and part-time study. Most students will include practical experience in the form of an internship in their study plan.
The Statistics major builds on a foundation in probability and statistical theory to provide practical training in statistical methods, study design, and data analysis. The major is appropriate background for graduate work, including doctoral studies in statistics, social science, and public health. The major also prepares students for careers where the analysis of data is of fundamental importance, including genetics, health policy, epidemiology, marketing, opinion polling, economics, finance and banking, government, drug development, and insurance. Students pursuing the major in statistics should meet with the director of undergraduate studies as early as possible to develop a study plan. The usual plan begins with the calculus-based introductory survey course, proceeds through core courses in probability theory and statistical inference, and then to elective courses that provide grounding in theory together with practical experience.
M.A. in Statistics
The M.A. program may serve as preparation for doctoral study in statistics or other quantitative fields, but it is designed primarily for individuals who seek a systematic study of statistical theory and statistical methods as preparation for a new career or to advance in their current position. Both full-time and part-time enrollment is possible, and many students enroll exclusively in evening courses. The student population ranges from new graduates to seasoned professionals, and contains a large proportion of international students. A variety of elective courses provide opportunities for concentrations in areas such as biostatistics, mathematical finance, and actuarial methods. Practical experience in the use of statistical packages is a feature of most of the advanced courses.
M.A. in Mathematics with a specialization in Mathematics of Finance
In conjunction with the Department of Mathematics, the Department of Statistics offers an M.A. in Mathematics with a specialization in the Mathematics of Finance. The program provides instruction in the advanced quantitative methods required for modern finance and draws on the diverse strengths of Columbia in stochastic processes, numerical methods, and application to finance. Topics covered include probability and random processes, statistics, partial differential equations, financial markets and instruments, valuation and hedging techniques, and computational and simulation methods.