New York University Steinhardt School of Culture, Education, and Human Development 20 courses 43 total credits
The Master of Science in Applied Statistics for Social Science Research (A3SR) provides students with rigorous training in applied statistics research techniques and strategies that can be applied to contemporary social, behavioral, and health science research. This MS program is a good choice for students who want to gain greater knowledge of statistics and its application to everyday problems and policies, and to sharpen their data-analysis and problem-solving skills. The A3SR curriculum provides students with a firm foundation in statistical modeling tools and theoretical perspectives common within the social, behavioral, and health sciences, while allowing the opportunity to pursue their own interests and develop specialized skills. It prepares students to become applied statisticians and data scientists in the public or private sector, as well as for further academic study in fields that rely on quantitative research. The concentrations and electives can be tailored to studentsβ substantive and methodological interests. A3SR faculty have particular strengths in causal inference, demography, missing data, model selection, multivariate analysis, multi-level modeling, networks, and surveys and sampling. They also have expertise on methods at the intersection between machine learning and statistics. Students are encouraged to work closely with faculty on research that ranges from applied statistical analysis to the development of customized statistical models. A dual degree option offers students interested in contributing to public policy the opportunity to develop both their quantitative skills and their policy analysis and public management expertise by completing both an MS in Applied Statistics at NYU Steinhardt and an MPA in Public and Nonprofit Management at the NYU Wagner Graduate School of Public Service in two years. The MS program focuses on understanding and applying advanced statistical techniques critical to policy issues across the social, behavioral, and health sciences. The MPA program, with its Public Policy Analysis specialization, provides students with key frameworks from economics and political science alongside important skills in management and finance, and sets them up to play a leading role in designing, implementing, and evaluating policy that better serves the public good.
Major Requirements
Core Requirements
Concentrations
Computational Methods Concentration:
| Code | Course Title | Credits |
|---|---|---|
| APSTA-GE 2123 | Bayesian Inference | 2 |
Concentrations
Choose 4 credits from the following:
| Code | Course Title | Credits |
|---|---|---|
| APSTA-GE 2013 | Missing Data | 2 |
| APSTA-GE 2011 | Supervised and Unsupervised Machine Learning | 2 |
| APSTA-GE 2042 | Multi-Level Modeling: Nested Data/Longitudinal Data | 3 |
Concentrations
Data Science for Social Impact Concentration:
| Code | Course Title | Credits |
|---|---|---|
| APSTA-GE 2062 | Ethics of Data Science | 3 |
| APSTA-GE 2355 | Data Science Translation: Writing and Visualization | 3 |
Concentrations
Select two of the following:
| Code | Course Title | Credits |
|---|---|---|
| APSTA-GE 2139 | Survey Research Methods | 3 |
| APSTA-GE 2094 | Modern Approaches in Measurement | 3 |
| APSTA-GE 2134 | Experimental & Quasi Experimental Design | 3 |
Culminating Experience
| Code | Course Title | Credits |
|---|---|---|
| APSTA-GE 2401 | Statistical Practice and Proficiency | 3 |
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