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Effective Spring 2018 - students entering in Fall 2017 may opt to follow this new curriculum. MS students following an earlier curriculum should contact their program advisor at ZicklinMSPrograms@baruch.cuny.edu or review the appropriate bulletin for the year they entered.

For additional program information see the Zicklin School website

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).

 

English Language Proficiency:*
Students who completed their undergraduate education in a non-English speaking country will be required to take non-credit bearing modules in Grammar Troubleshooting and American English Pronunciation offered by the Division of Continuing and Professional Studies. These modules may be waived based on a waiver exam. The modules are not required for students who completed a four-year degree in an English-speaking country.

Preliminary Courses    (9 credits)

Students with appropriate academic background will be able to reduce the number of credits in preliminary requirements. Grades in undergraduate mathematics courses are not calculated in the grade point average.

Calculus I3 credits
Calculus II3 credits
Applied Statistical Analysis for Business Decisions3 credits
*MTH 2610 and MTH 3010 are undergraduate courses. Entering students are strongly adviced to complete a minimum of six credits of calculus before starting the MS programs in Statistics, in order to waive these math requirements.
Courses in Specialization    (31.5 credits)

Required for the General and Data Science Track   (13.5 credits)

Business Communication I1.5 credits
Applied Regression Analysis3 credits
Applied Probability3 credits
Foundations of Statistical Inference3 credits
Software Tools for Data Analysis  

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3 credits
General Track: Choose 12 credits from the following courses:
Advanced Data Mining for Business Analytics3 credits
Time Series: Forecasting and Statistical Modeling3 credits
Multivariate Statistical Methods3 credits
Analysis of Categorical and Ordinal Data3 credits
Statistical Methods in Sampling and Auditing3 credits
Advanced Linear Models3 credits
Financial Statistics3 credits
Experimental Design for Business3 credits

   CIS 9760 

Big Data Technologies (cross-listed as MTH 9760 & STA 9760)3 credits
Stochastic Processes for Business Applications 

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3 credits
Special Topics in Statistics1 credit
Special Topics in Statistics1.5 credits
Special Topics in Statistics2 credits

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Special Topics in Statistics3 credits

   STA 9890**

Statistical Learning for Data Mining3 credits

   STA 9891**

Machine Learning for Data Mining3 credits

   STA 9796 

Statistical Natural Language Processing1.5 credits

   STA 9797 

Advanced Data Analysis1.5 credits
Advanced Statistical Computing   

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3 credits

Data Science Track: Choose 12 credits from the following courses:

 Additional Required Courses for the Data Science Track

   STA 9705 

Multivariate Statistical Methods3 credits

   STA 9890** 

Statistical Learning for Data Mining3 credits

   STA 9891** 

Machine Learning for Data Mining3 credits
  Choose at least 3 credits from the following courses: 

   CIS 9760 

Big Data Technologies (cross-listed as MTH 9760 & STA 9760)3 credits

   STA 9796 

Statistical Natural Language Processing1.5 credits

   STA 9797 

Advanced Data Analysis1.5 credits
 **Students may not receive credit for STA 9690 and STA 9890 and/or STA 9891.

 Business Electives for General Track and Data Science Track (6 credits):

Choose 9000-level courses from the graduate offerings of the Zicklin School of Business, with the exception of STA 9708; courses applied towards a prior master's degree; or courses that do not allow credit to be given for both that course and another statistics course. Students may take additional statistics courses as their business electives.

 

Note that BUS 9551 is effective for all MS-Statistics students admitted in spring 2016 or later. Students admitted prior to spring 2016 should consult their preliminary course evaluation and/or waiver exam results, since other requirements and conditions may apply.

 

 

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