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.  Each student’s Faculty Adviser must approve all courses.  If a course is not on this list, the syllabus should be supplied to the Faculty Adviser to review and decide if it is appropriate for an individual student to count for graduation.

If there is a course not on this list, but should be approved for ALL students in the MA Statistics Program, the syllabus should be reviewed by the Faculty Adviser first and then sent to the Program Director to approve.  If approved, it will be added to this list of Approved Electives.

Courses change all the time. Just because something is on our approved list does not mean it is available for our students or that it is offered every semester. Check the Course Directory for up-to-date information on what courses are offered each semester.

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
STATGR5206Statistical Computing and Intro to Data Science
STATGR5207Elementary Stochastic Processes
STATGR5221Time Series Analysis
STATGR5222Nonparametric Statistics
STATGR5223Multivariate Stat Inference
STATGR5224Bayesian Statistics
STATGR5231Survival Analysis
STATGR5232Generalized Linear Models
STATGR5233Regression and Multi-Level Models
STATGR5234Sample Surveys
STATGR5241Statistical Machine Learning
STATGR5242Advanced Machine Learning*
STATGR5243Applied Data Science
STATGR5261Statistical Methods in Finance
STATGR5262Stochastic Processes for Finance
STATGR5263Stat Inf/Time-Series Modeling
STATGR5264Stochastic Processes Applications I
STATGR5265Stochastic Methods in Finance
STATGR5293Topics 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

CourseCourse Title
PUBH P8108Survival Analysis (PUBH P6103/4, STAT GR5203, GR5204 and GR5205)
PUBH P8116Design of Medical Experiments (PUBH P6103/4, STAT GR5203, 5204 and 5205)
PUBH P8121Generalized Linear Models (PUBH P6103/4, STAT GR5203, GR5204, and GR5205)
PUBH P8139Theoretical Genetic Modeling (PUBH P6103/4)
PUBH P8140The randomized clinical trial I (PUBH P6103/4)
PUBH P8142The 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.

CourseCourse Title
IEOR E4403Advanced Engineering and Corporate Economics
IEOR E4404Simulation
IEOR E4407Game-Theoretical Models of Operations
IEOR E4412Quality Control and Management
IEOR E4700Introduction to Financial Engineering

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

Mathematics Courses

CourseCourse Title
MATH GU4061Introduction to Modern Analysis I
MATH GU4062Introduction to Modern Analysis II
MATH GR5010Introduction to the Theory of Mathematical Finance*
MATH GR5220Quantitative Methods in Investment Management
MATH G5360Math Mthds-Fin Price Analysis
MATH GR5280Capital Markets & Invest
MATH GR5380Multi-Asset Portfolio Mgmt
MATH GR5340Fixed Income Portfolio Mgmt
MATH GR5300Hedge Funds Strategies & Risk
MATH GR5320Financial Risk Management & Regulation
MATH GR6151Analysis & Probability I
MATH GU4155Probability Theory
MATH GR6307Algebraic Topology
MATH GR6308Algebraic Topology II
MATH GR5030Numerical 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

CourseCourse Title
ECON GU4415Game Theory
ECON GU4301Economic 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”).

CourseCourse Title
FINC B8306Capital Markets & Investments
FINC B8307Advanced Corporate Finance
FINC B8308Debt Markets
FINC B8312Advanced Derivatives
FINC B8310Advanced International Corporate Finance
FINC B8318Investment Banking Tax Factors
FINC B8323Asset Management
FINC B8325Mergers & Acquisitions
FINC B8326Capital Markets Regulation
FINC B8333Real Estate Capital Markets
FINC B8347Financial Crises and Regulatory Responses
FINC B8348Emerging Financial Markets
FINC B8362Project Finance
FINC B8368Security Analysis
FINC B8384Equity Derivatives
FINC B8394Private Equity: the asset class, its investments & its markets
FINC B8396Institutional Investing: Alternative Assets in Pension Plans
FINC B8423Investor Influence on Corporate Sustainability
FINC B8424Competitive Advantage in Investing
BUEC B8250Global 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

CourseCourse Title
PS5821Actuarial Methods I
(By permission only by Faculty Adviser; must have demonstrated interest in AS)
PS5822Actuarial Methods II (By permission only)
PS5823Actuarial Models
PS5830Models for Financial Economics
(formerly known as Stochastic Processes for Actuaries) (By Permission Only)
PS5846Quantitative 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.

CourseCourse Title
U6506Data Science & Public Policy
APMA E4990 Introduction to Data Science in Industry
BINF G4006Translational Bioinformatics
COMS W4111Introduction to Databases*
COMS W4121Computer Systems for Data Science (Spring course only)
CSOR W4246Algorithms for Data Science**
ECBM E6040Neural Networks and Deep Learning
EECS E6720Bayesian Mod Machine Learning
EECS E6893Big Data Analytics
EECS E6894Deep 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).  These courses are not open to Statistics students during pre-registration.  There is a new hybrid version of COMS W4111 Sec H03 that  MA Statistics students may consider.  Enrollment is determined by the CS Department and 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. 


FINANCE

GR5221Time Series Analysis
GR5207Elementary Stochastic Processes
GR5264Stochastic Processes-Applications I
GR5263Stat Inf/Time Series Modelling
GR5265Stochastic Methods in Finance
GR5261Statistical Methods in Finance

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

DATA SCIENCE SEQUENCE IN STATISTICS

GR5206Stat Computing & Intro to Data Science (prerequisite for GR5241)
GR5241Statistical Machine Learning (prerequisite for GR5242)
GR5242Advanced 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.

PHARMACEUTICAL INDUSTRY OR PUBLIC HEALTH

GR5232Generalized Linear Models
GR5222Non-Parametric Statistics
GR5231Survival Analysis

In addition to approved courses from Biostatistics and Epidemiology.

ACTUARIAL SCIENCE and THE INSURANCE INDUSTRY

GR5231Survival Analysis
PS5823Actuarial Models
GR5207Elementary Stochastic Processes

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

Ph.D. TRACK

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.