Total Points Required: 34 minimum; 34-47 variable
This is a variable-credit program in which you can take a minimum of 34 credits and a maximum of 47 credits. If you are entering the program with prior statistical training, the accelerated, lower credit option may be ideal for you. Most students with no prior statistical experience will take around 41 credits.
The program consists of theoretical foundations, statistical inference and generalized linear models, causal inference, survey research methods, multilevel modeling, applied statistics electives, and unrestricted electives. A statistical consulting research seminar and internship provide practical learning experiences.
Required Courses: 29-34 credits
|Foundations in Social Research:||Units|
|RESCH-GE 2132: Empirical Research Methods||3|
Students may choose to replace this requirement with a methods course being offered in their specific area of studies, with advisor approval.
SOC-GA 1301 Design of Social Research (Sociology)
|Inference and Regression:|
|APSTA-GE 2003: Intermediate Quantitative Methods*
can be replaced by STAT-GB 2301: Regression and Multivariate Data Analysis
|APSTA-GE 2004: Advanced Modeling I: Topics in Multivariate Analysis*||2|
|APSTA-GE 2012: Causal Inference||3|
|APSTA-GE 2122: Applied Statistical Modeling and Inference||3|
|APSTA-GE 2044: Generalized Linear Models and Extensions||2|
|* indicates that the student with equivalent prior coursework may place out of this course.|
|Theoretical and Practical Issues in Survey Methodology:|
|RESCH-GE 2139: Survey Research I||3|
|APSTA-GE 2110: Applied Statistics: Using Large Databases in Education Research***
APSTA-GE.2017: Adv. Topics in Quant. Meths: Educational Data Science Practicum***
|APSTA-GE 2042: Multilevel Models: Nested Data||2|
|APSTA-GE 2013: Advanced Topics in Quantitative Methods: Missing Data||2|
|Statistical Consulting Research Seminar and Internship:|
|APSTA-GE 2300 Internship**||1-4***|
|APSTA-GE 2401: Statistical Consulting Research Seminar||3|
|* indicates that the student with equivalent prior coursework may place out of this course.
** Students are advised that internships must be approved by a program advisor and will be assessed in terms of content and rigor.
*** The choice between APSTA-GE 2110 and APSTA-GE 2017 and the number of credits required for the internship, APSTA-GE 2300, are based on each student's prior knowledge and experience. These decisions and made by advisement.
Applied Statistics Electives: 4-8 points
Students are required to take two electives with significant applied statistical content (e.g., measurement models, computational statistics. Courses may be taken within or outside the program.
|WIthin-Program Applied Statistics Electives |
(may count in required course points for those placing out of the above required course, except those *)
|APSTA-GE.2011: Adv. Topics in Quantitative Methods: Classification and Clustering||2|
|APSTA-GE.2015: Adv. Topics in Quantitative Methods: Applied Spatial Statistics||2|
|APSTA-GE.2016: Adv. Topics in Quant. Meths: Factor Scoring and Practical Issues in Scaling||2|
|APSTA-GE.2017: Adv. Topics in Quant. Meths: Educational Data Science Practicum||2|
|APSTA-GE.2094: Factor Analysis and Structural Equation Modeling||3|
|APSTA-GE.2998: Adv. Methods in Health and Policy Res.: Survival Analysis||2|
|APSTA-GE.2040/2041: Multilevel Models (course + practicum)||3|
|Outside-Program Applied Statistics Electives|
|APSY-GE.2141: Measurement: Modern Test Theory|
|APSY-GE.2142: Measurement and Evaluation: Psychometric Theory|
|Courant Institute of Mathematical Sciences, School of Medicine, Faculty of Arts and Science, or Tandon School of Engineering:|
MA-GY.7763: Topics in Statistics: Data Mining and Machine Learning
|MATH-GA 2840: Advanced Topics in Applied Mathematics-Dynamic Computational Statistical models for Socio-economic and Geo-political Systems|
|CSCI-GA-256: Machine Learning and Pattern Recognition|
|CSCI-GA 1180 Mathematical Techniques for Cs Applications|
|DS-GA 1002 Statistical and Mathematical Methods|
|DS-GA 1003 Machine Learning|
|DS-GA 1004 Big Data
|DS-GA 3001-04 Text as Data|
|EHSC-GA 2339 Introduction to Bayesian Modeling|
|For more courses, visit the Data Science curriculum website . Please note some of the courses offered through Data Science may have substantial pre-requisites in mathematics and computer science; further, open seats in classes offered in that program are limited.|
|Department of Politics, Faculty of Arts and Science:|
|POL-GA 3200: Topics in Network Analysis|
|Department of Psychology, Faculty of Arts and Science:|
|PSYCH-GA 2243 Psychometric Theory|
|PSYCH-GA 2247: Structural Equation Methods|
|PSYCH-GA 2248: Methods for the Analysis of Change|
|Department of Sociology, Faculty of Arts and Science:|
|SOC-GA 2314: Longitudinal Statistics|
|SOC-GA 2306: Event History Analysis|
|Department of Economics, Stern School of Business:|
|ECON-GB 3351: Econometrics I|
|ECON-GB 9912: Econometric Analysis of Panel Data|
|Program of Statistics, Stern School of Business:|
|STAT-GB 2302: Forecasting Time Series Data|
|STAT-GB 2308: Applied Stochastic Processes For Financial Models|
|STAT-GB 4310: Statistics for Social Data|
|Robert F. Wagner Graduate School of Public Service:|
|PADM-GP.2875: Estimating Impacts in Policy Research|
|PADM-GP.2171: Program Analysis and Evaluation|
For all Stern courses: view the cross-registration process and form required here.
For all Wagner courses (PADM-GP): submit a course registration request here.
Unrestricted Electives: 6-8 points
The two unrestricted electives may be taken from departments across the entire university according to your own interests, with adviser approval. We recommend EDPLY-GE 2030 Education and Social Policy.