Applied Statistics and Decision Making (M.S.)
Are you enticed by the fact that statistics experts are getting hired everywhere, but you feel that your true calling lies in biomedical research? Do you have a knack for numbers but a devotion to public policy?
These unique combinations find a home in the Gabelli School’s Master of Science in Applied Statistics and Decision Making (M.S.S.D.) program. The curriculum is general enough to offer a solid foundation in data science and flexible enough to marry it to the specific area that interests a student most—whether it’s a business discipline or not.
This works in your favor in ways you might not even realize: Companies are looking for candidates who demonstrate a clear passion for their chosen field.
Fordham M.S.S.D. students can choose between a one-year, full-time program, or a part-time, two-year option that accommodates work schedules or internships.
To learn more about the M.S. in Applied Statistics and Decision Making, visit the Fordham website.
CIP Code
27.0501 - Statistics, General.
You can use the CIP code to learn more about career paths associated with this field of study and, for international students, possible post-graduation visa extensions. Learn more about CIP codes and other information resources.
Prerequisites
M.S.S.D. students need basic knowledge of statistics and calculus when they start the program. If you don’t have that, we can help. Students who need prerequisites can take them at the Gabelli School prior to beginning the M.S.S.D. coursework.
Curriculum
The schedule below illustrates how the M.S.S.D. is structured for a full-time student who aims to complete the degree in one year. Part-time students work with our program director and academic advisor to stretch the M.S.S.D. over a longer time frame that makes sense for their professional schedules. This is a ten course, 30-credit program, with five required courses and a choice of five electives.
| Fall | Credits | |
|---|---|---|
| SDGB 7844 | Stat Methods and Comp I | 3 |
| SDGB 7841 | Statistical Theory I | 3 |
| SDGB 7843 | Judgment and Decision Making | 3 |
| Six credits of electives from the courses in the table below | 6 | |
| Credits | 15 | |
| Spring | ||
| SDGB 7840 | Applied Regression Analysis | 3 |
| SDGB 7842 | Statistical Theory II | 3 |
| Nine credits of electives from the courses in the table below | 9 | |
| Credits | 15 | |
| Total Credits | 30 | |
Elective Courses
Courses in this group have the ASDM attribute.
Students may consult with the Faculty Program Director and Academic Advisor to seek approval to fulfill electives among SDGB, FNGB, GFGB, QFGB, and ISGB courses. Students are responsible for completing any course prerequisites if necessary.
| Course | Title | Credits |
|---|---|---|
| ACGB 6111 | Financial Accounting & Reporting Data Analysis | 3 |
| ACGB 7125 | Financial Statement Analysis | 3 |
| ACGB 7128 | Advanced Financial Statement Analysis | 3 |
| ACGB 719F | Accounting Controls | 3 |
| ACGB 719G | Audit Data Analytics | 3 |
| ACGB 719H | IT Audit and Information Assurance | 3 |
| ACGB 719J | Industry Analysis and Strategic Planning | 3 |
| ACGB 819A | Valuation and Modeling for Accounting | 1.5 |
| CISC 5004 | Computer Programming C++ | 3 |
| CISC 5350 | Financial Programming | 3 |
| CISC 5790 | Data Mining | 3 |
| DGGB 7850 | Forecasting Models | 3 |
| ECON 6020 | Macroeconomic Theory I | 3 |
| ECON 6950 | Financial Econometrics | 3 |
| FNGB 749A | Financial Modeling | 3 |
| ISGB 7967 | Data Mining for Business | 3 |
| ISGB 7975 | Business Analytics for Managers | 3 |
| MIGB 7732 | Data-Driven Marketing Decisions | 3 |
| MKGB 7730 | Research Methods | 3 |
| MKGB 779I | Data-Driven Marketing Decisions | 3 |
| MKGB 8701 | Marketing Analytics | 1.5 |
| PSGE 7210 | Experimental Design | 3 |
| PSGE 7213 | Application of Multivariate Techniques in Education and Psychology | 3 |
| PSYC 7835 | Categorical Data Analysis | 3 |
| PSYC 7965 | Experimental Design | 3 |
| QFGB 8925 | Simulation Applications | 2 |
| QFGB 8935 | Risk Management | 2 |