MS in Applied Statistics

Degree Requirements

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 42 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.

Please note that these requirements are effective for the Fall 2016 incoming class. Subsequent incoming students may be subject to different program requirements.

See brief course descriptions. See links to syllabi for courses offered in 2016-17. Get links to syllabi for previous years.

Required Courses: 30-35 credits


RESCH-GE 2132: Empirical Research Methods

Students may choose to replace this requirement with a methods course being offered in their specific area of studies, with advisor approval.


APSTA-GE 2331 Data Science for Social Impact (Applied Statistics)

SOC-GA 1301 Design of Social Research  (Sociology)
PHDSW-GS 3064 Social and Behavioral Intervention Research (Social Work)
PSYCH-GA 2067 Applied Research Methods (Psychology)
GPH-GU 2950 Methods in Community Health Research (Public Health)
ECON-GA 1003 Microeconomic Theory (Economics)+
ECON-GA 1603 Economic Development I (Economics)+
CUSP-GX 5003 Principles of Urban Informatics (Data management & data ethics)
DA-GA 3001 Spec. Topics: Law and Ethics for Data Managers

+For ECON courses, email advisor with transcript proving prerequisite equivalency and it will be reviewed by the ECON department

Inference and Regression: 
APSTA-GE 2003: Intermediate Quantitative Methods*
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**  4
APSTA-GE 2044: Generalized Linear Models and Extensions 2
* indicates that the student with equivalent prior coursework may place out of this course.
** APSTA-GE 2351 and APSTA-GE 2352 (or equivalent) are advised as pre-requisites
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***
Multilevel Models: 
APSTA-GE 2042: Multilevel Models: Nested Data 2
Missing Data: 
APSTA-GE 2013: Advanced Topics in Quantitative Methods: Missing Data 2
Statistical Consulting Research Seminar and Internship: 
APSTA-GE 2310 Internship+ 2-4***
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 2310, 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.  Some courses may be taken outside the program.

WIthin-Program Applied Statistics Electives
(may count in required course points for those placing out of the above required course, except *)
APSTA-GE.2011: Adv. Topics in Quantitative Methods: Classification and Clustering 2
APSTA-GE.2013: Missing Data - if not required for your program, may be an elective 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.2040/2041: Multilevel Models (course + practicum) - if not required, may be an elective 3
APSTA-GE.2094: Factor Analysis and Structural Equation Modeling 3
APSTA-GE.2351/2352: Practicum in Applied Probablity/Computational Statistics may be required; see APSTA-GE 2122, above  


Out of program electives:
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
DS-GA 1002 Statistical and Mathematical Methods
DS-GA 1003 Machine Learning 
DS-GA 1004 Big 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 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
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
INFO-GB 3335: Data Mining for Business Analytics

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.

Unrestricted ElectivesPoints
Elective 1 3-4
Elective 2 3-4