Approved Courses 

Admittance into any course below is not guaranteed.  All courses are subject to availability. 

The approved courses listed below are available for elective credit in the M.A. in Statistics Program. (Please also review non-approved courses.) The MA Program requires a total of six elective courses, of which at least three must be offered by the Statistics Department.  For review of the four required core courses please visit this web page. Students should always confer with their Faculty Adviser prior to selecting electives each semester.

A course not on this list may be approved as an elective when the syllabus is reviewed and deemed appropriate by the Faculty Adviser or Program Director. 

Topics and seminar courses are generally not approved, although Topics in Modern Statistics GR5293** may be taken once as an approved elective.  Statistics courses offered in other departments, other than the ones listed below, are generally not approved. 

Course Registration:  Statistics Elective Courses

Statistics Elective Courses (must complete a minimum of 3 total)

STAT # Course Title
STAT GR5206 Statistical Computing and Intro to Data Science
STAT GR5207 Elementary Stochastic Processes
STAT GR5221 Time Series Analysis
STAT GR5222 Nonparametric Statistics
STAT GR5223 Multivariate Stat Inference
STAT GR5224 Bayesian Statistics
STAT GR5231 Survival Analysis
STAT GR5232 Generalized Linear Models
STAT GR5233 Regression and Multi-Level Models
STAT GR5234 Sample Surveys
STAT GR5241 Statistical Machine Learning
STAT GR5242 Advanced Machine Learning*
STAT GR5243 Applied Data Science
STAT GR5261 Statistical Methods in Finance
STAT GR5262 Stochastic Processes for Finance
STAT GR5263 Stat Inf/Time-Series Modeling
STAT GR5264 Stochastic Processes Applications I
STAT GR5265 Stochastic Methods in Finance
STAT GR5293 Topics in Modern Statistics**
**The topics course GR5293 may only count ONCE towards the MA Program approved electives.  

Cross Registration: Approved Courses in other Departments

Admittance into any course below is not guaranteed.  All courses are subject to availability, especially those offered from other departments.  Read HERE for more details about cross registration. 

School of Public Health Courses

Course Course Title
PUBH P8108 Survival Analysis (PUBH P6103/4, STAT GR5203, GR5204 and GR5205)
PUBH P8116 Design of Medical Experiments (PUBH P6103/4, STAT GR5203, 5204 and 5205)
PUBH P8121 Generalized Linear Models (PUBH P6103/4, STAT GR5203, GR5204, and GR5205)
PUBH P8139 Theoretical Genetic Modeling (PUBH P6103/4)
PUBH P8140 The randomized clinical trial I (PUBH P6103/4)
PUBH P8142 The randomized clinical trial II (PUBH P6103/4, P8140)

Notes: The courses in parentheses are pre-requisite courses.  


Industrial Engineering and Operations Research (IEOR) Courses

For information on how to cross-register for Industrial Engineering and Operations Research click here.  

Course Course Title
IEOR E4403 Advanced Engineering and Corporate Economics
IEOR E4404 Simulation
IEOR E4407 Game-Theoretical Models of Operations
IEOR E4412 Quality Control and Management
IEOR E4700 Introduction to Financial Engineering

Note: please click here for information on how to cross register for their courses.  


Mathematics Courses

Course Course Title
MATH GU4061 Introduction to Modern Analysis I
MATH GU4062 Introduction to Modern Analysis II
MATH GR5010 Introduction to the Theory of Mathematical Finance*
MATH GR5220 Quantitative Methods in Investment Management
MATH G5360 Math Mthds-Fin Price Analysis
MATH GR5280 Capital Markets & Invest
MATH GR5380 Multi-Asset Portfolio Mgmt
MATH GR5340 Fixed Income Portfolio Mgmt
MATH GR5300 Hedge Funds Strategies & Risk
MATH GR5320 Financial Risk Management & Regulation
MATH GR6151 Analysis & Probability I
MATH GU4155   Probability Theory
MATH GR6307 Algebraic Topology
MATH GR6308 Algebraic Topology II
MATH GR5030   Numerical Methods in Finance

*This course is easier for MA Statistics students to get into during the spring semester option

Applied Mathematics Course

APMA 4300 – Introduction to Numerical Methods

Economics Courses

Course Course Title
ECON GU4415 Game Theory
ECON GU4301 Economic Growth & Development


Finance and Business Economics Courses at Columbia Business School

For specific instructions on how to cross-register for classes at Columbia Business School click here (Most courses have a prerequisite of Capital Markets “FINC B8306/ MATH G4076” or “waiver exam”). 


Course Title

FINC B8306

Capital Markets & Investments

FINC B8307

Advanced Corporate Finance

FINC B8308

Debt Markets

FINC B8312

Advanced Derivatives

FINC B8310

Advanced International Corporate Finance

FINC B8318

Investment Banking Tax Factors

FINC B8323

Asset Management

FINC B8325

Mergers & Acquisitions

FINC B8326

Capital Markets Regulation

FINC B8333

Real Estate Capital Markets

FINC B8347

Financial Crises and Regulatory Responses

FINC B8348

Emerging Financial Markets

FINC B8362

Project Finance

FINC B8368

Security Analysis

FINC B8384

Equity Derivatives

FINC B8394

Private Equity: the asset class, its investments & its markets

FINC B8396

Institutional Investing: Alternative Assets in Pension Plans

FINC B8423

Investor Influence on Corporate Sustainability

FINC B8424

Competitive Advantage in Investing

BUEC B8250

Global Economic Environment II

Note: most courses have a prerequisite of Capital Markets (FINC B8306/ MATH GR5280 (formerly G4076) or waiver exam). Click here for more information.  


Actuarial Science Courses

Course Course Title


Actuarial Methods I
(By permission only by Faculty Adviser; must have demonstrated interest in AS)  


Actuarial Methods II (By permission only)    


Actuarial Models  


Models for Financial Economics
(formerly known as Stochastic Processes for Actuaries) (By Permission Only)


Quantitative Risk Management

Machine Learning/Data Science/Computer Science Courses 

Important Note: Students may take up to two courses from the list below. Faculty advisers must be consulted for approval to take additional Machine Learning or Data Science courses outside of the Statistics Program. Students must consult with Faculty Advisers about potential overlap in Data Science/Machine Learning courses when exploring courses not on the list below. Faculty approval is required. 


Course Title

APMA E4990  Introduction to Data Science in Industry

BINF G4006

Translational Bioinformatics 

COMS W4111

Introduction to Databases*

COMS W4121

Computer Systems for Data Science (Spring course only)

CSOR W4246

Algorithms for Data Science**

ECBM E4040

Neural Networks and Deep Learning

EECS E6720 Bayesian Mod Machine Learning
EECS E6893 Big Data Analytics
EECS E6894 Deep Learning for Computer Vision and Natural Language Processing

*MA Statistics students can register on a waitlist for Computer Science courses via SSOL during regular registration (the week before the Change of Program Period).  There is also a new hybrid version of COMS W4111 Sec H01 that will be open to MA Statistics students. This is the more likely option for our students to get into (as of Fall 18). These courses are not open to Statistics students during pre-registration.  Enrollment is determined by the CS Department based upon seniority and need for the course as a graduation requirement.  Enrollment from the waitlist is not guaranteed. 

Statistics Electives by Interest Area

Below are some possible electives a student might select based upon interest area. Please note these courses are recommended as a helpful guide in course selection; however, they are not required.

Admittance into any course below is not guaranteed.  All courses are subject to availability. 


GR5221  Time Series Analysis
GR5207  Elementary Stochastic Processes
GR5264  Stochastic Processes-Applications I
GR5263  Stat Inf/Time Series Modelling
GR5265  Stochastic Methods in Finance
GR5261 Statistical Methods in Finance

In addition to approved courses from the Business School, Mathematics of Finance, & Related Programs.


GR5206 Stat Computing & Intro to Data Science (prerequisite for GR5241)
GR5241 Statistical Machine Learning (prerequisite for GR5242)
GR5242 Advanced Machine Learning 

*Data Science Sequence – The Data Science sequence includes GR5206 offered in the fall which is a prerequisite for GR5241 offered in the spring. Both courses are a prerequisite for the course, GR5242: Advanced Machine Learning.


GR5232  Generalized Linear Models
GR5222  Non-Parametric Statistics
GR5231  Survival Analysis

In addition to approved courses from Biostatistics and Epidemiology.


GR5231  Survival Analysis
PS5823  Actuarial Models
GR5207  Elementary Stochastic Processes

In addition to approved courses from Economics, Actuarial Science, & the Business School.


Please confer with your Faculty Adviser. 


Non-Approved Courses

The following courses are NOT approved for the Statistics MA degree requirement:

  • 3000 level courses
  • Courses offered by the Applied Analytics Program in the School of Professional Studies 
  • STAT GU4281 or K5281 – Theory of Interest
  • STAT GU4282 – Linear Regression and Time Series Models
  • STAT GR5705 – Intro to Data Science; STAT GR5701 – Prob & Statistics;  GR5703 – Stat Inference and Modeling (Courses for Data Science Institute students only)
  • SIEO W4150 – Intro Prob & Stat Inference
  • IEOR E4106 – Stochastic Models
  • IEOR E4540 – Data Mining for Engineers
  • ECON W4412 – Ad Econometrics or other 4000-level Econometrics courses
  • ECON W4413 – Econometrics of Time Series
  • QMSS W5067 – Natural Language Processing
  • Finance 6000 – level courses
  • Biostat 6000 – level courses

Many topics and seminar courses are not approved to fulfill the MA degree requirement. 

Students may take such courses in addition to the ten courses required for the degree program. 

For example,  COMS W4995 / COMS E6998

For courses not listed above, students should confirm with their Faculty Adviser before registering.