The Master of Science in Statistics teaches you to apply key aspects of quantitative models to decision making across a variety of industries. With an MS in Statistics, you will gain the knowledge essential for success as a statistics professional and develop the necessary skills to help meet modern business demands for statistical models, business analytics, and data mining.
Program Highlights
- Average completion is 3-4 semesters
- Flexible scheduling allows you to switch between part-time and full-time course loads
- Qualifies for Department of Homeland Security OPT Extension for STEM International Students
Preliminary Course Requirements
Students are strongly advised to complete a minimum of six credits of undergraduate calculus (Calculus I & II) before beginning graduate coursework.
Visa Extension for STEM International Students
The Master’s in Statistics conforms to the U.S. Department of Homeland Security’s STEM (Science, Technology, Engineering, Math) program that qualifies eligible international graduates on student visas for an optional practical training extension of 24-months. Find out more here.
Preliminary Courses and Waivers
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. |
| |
|
Credits |
| MTH 2610* |
Calculus I |
3 |
| MTH 3010* |
Calculus II |
3 |
| STA 9708 |
Applied Statistical Analysis for Business Decisions |
3 |
| *MTH 2610 and MTH 3010 are undergraduate courses. Entering students are strongly advised to complete a minimum of six credits of calculus before starting the MS programs in Statistics, in order to waive these math requirements. |
Waivers are based on prior coursework:
MTH 2160 is waived based on 3-credits of an undergraduate calculus (not pre-calculus) course with a minimum C- grade.
MTH 3010 is waived based on 3-credits of an advanced calculus course with a minimum of C- grade.
STA 9708 is waived based on 6-credits of statistics with a minimum grade average of B-.
MS in Statistics - General Track
This curriculum is effective for students entering in Spring 2020. Students who entered prior to Spring 2020 should review the Graduate Bulletin or contact a program advisor to confirm their degree requirements.
Courses in Specialization (31.5 credits)
Required for General Track: (13.5 credits)
|
| BUS 9551 |
Business Communication I |
1.5 |
| STA 9700 |
Applied Regression Analysis |
3 |
| STA 9715 |
Applied Probability |
3 |
| STA 9719 |
Foundations of Statistical Inference |
3 |
| STA 9750 (OPR 9750 ) |
Software Tools for Data Analysis |
3 |
General Track Electives
Choose 12 – 18 credits from the list below for the MS in Statistics program. If you plan to specialize in Data Science, please ensure that you take the appropriate electives specific to that track.
|
| CIS/STA 9665 |
Applied Natural Language Processing |
3 |
| STA 9701 |
Time Series: Forecasting and Statistical Modeling |
3 |
| STA 9705 |
Multivariate Statistical Methods |
3 |
| STA 9706 |
Analysis of Categorical and Ordinal Data |
3 |
| STA 9710 |
Statistical Methods in Sampling and Auditing |
3 |
| STA 9712 |
Advanced Linear Models |
3 |
| STA 9713 |
Financial Statistics |
3 |
| STA 9714 |
Experimental Design for Business |
3 |
| CIS/STA 9760 |
Big Data Technologies |
3 |
| STA 9783 (OPR 9783) |
Stochastics Processes for Business Applications |
3 |
| STA 9791 |
Special Topics in Statistics |
1 |
| STA 9792 |
Special Topics in Statistics |
1.5 |
| STA 9793 |
Special Topics in Statistics |
2 |
| STA 9794 |
Special Topics in Statistics |
3 |
| STA 9797 |
Advanced Data Analysis |
3 |
| STA 9850 (OPR 9850 ) |
Advanced Statistical Computing |
3 |
| STA 9890* |
Statistical Learning for Data Mining |
3 |
| STA 9891* |
Machine Learning for Data Mining |
3 |
Business Electives for General Track (6 credits):
|
| Choose up to 6 credits of 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. |
MS in Statistics - Data Science Track
This curriculum is effective for students entering in Spring 2020. Students who entered prior to Spring 2020 should review the Graduate Bulletin or contact a program advisor to confirm their degree requirements.
Courses in Specialization (31.5 credits)
Required for Data Science Track: (13.5 credits)
|
| BUS 9551 |
Business Communication I |
1.5 |
| STA 9700 |
Applied Regression Analysis |
3 |
| STA 9715 |
Applied Probability |
3 |
| STA 9719 |
Foundations of Statistical Inference |
3 |
| STA 9750 (OPR 9750 ) |
Software Tools for Data Analysis |
3 |
Data Science Track
Complete the 9 credits listed below:
|
| STA 9705 |
Multivariate Statistical Methods |
3 |
| STA 9890 |
Statistical Learning for Data Mining |
3 |
| STA 9891 |
Machine Learning for Data Mining |
3 |
Choose at least 3 credits from the following courses:
|
| CIS/STA 9760 |
Big Data Technologies |
3 |
| STA 9797 |
Advanced Data Analysis |
3 |
| CIS/STA 9665 |
Applied Natural Language Processing |
3 |
| |
Business Electives for Data Science Track (6 credits):
|
| Choose up to 6 credits of 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. |
Office of Graduate Admissions
Address: 151 E. 25th St. Room 820 (between Lexington and Third Avenues)
Phone: (646) 312-1300
Fax: (646) 312-1301
Website: Graduate Admissions
