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Statistics

Overview

Official Name of Program

Statistics

Plan Code

STAT-MS

Department(s) Sponsoring Program

Career

Graduate

Degree Designation

MS - Master of Science

HEGIS Code

0503.00

NYSED Program Code

79229 - STAT-MS

CIP Code

27.0501

The Master of Science in Statistics is designed to train students in the design and application of quantitative models to decision making in business, finance, pharmaceutical and other industries, and government.  The MS program provides students with the concepts and skills that form the fundamental base of knowledge essential to statistics professionals in today's sophisticated business environment including the technical background and capabilities required for the newer approaches to overall business analytics and data mining. The MS program is designed to provide a concentrated, in-depth study of the field for those who wish to be technical specialists in statistics.  Students completing the MS degree successfully go on to careers as statisticians and sometimes continue to pursue a Ph.D. in statistics. The MS is a 31.5 credit program consisting largely of statistics courses and some related business courses which can be completed either part-time or full-time. The MS program conforms with the DHS - STEM program so that international students who graduate from the MS program may be eligible for an additional 24-month extension on their optional practical training (OPT).

MS in Statistics Program Learning Goals

General Statistical Competence

Students will be able to apply appropriate probability models and statistical techniques when analyzing problems form business and the other fields.

Statistical Practice

Students will become familiar with the standard tools of statistical practice for multiple regression, along with the tools of a subset of specialized statistical areas such as multivariate analysis, applied sampling, time series analysis, experimental design, data mining, categorical analysis, and/or stochastic processes.

Technology Competency

Students will learn to use one or more of the benchmark statistical software platforms, such as SAS or R.


Requirements