Program Category: 
M.A. Programs
Richard Davis

Degree Programs: Full-Time/Part-Time: Free-Standing M.A.

M.A. Executive Director: Alysa Turkowitz
M.A. Program Director: Demissie Alemayehu

The Department of Statistics offers programs of instruction that include theoretical and applied statistics and probability. The Department also offers cooperative programs in operations research with the Fu Foundation School of Engineering and Applied Science, in the Mathematics of Finance with the Department of Mathematics, in Actuarial Science with the School of Professional Studies, and in Quantitative Methods in Social Science with the Institute for Social and Economic Research and Policy. Columbia University and the New York area are notable for wide-ranging opportunities for the application of statistics. The Department maintains ties with industry, Wall Street, and medical and basic science researchers in New York and also helps to serve the statistical needs of the University community. There is a continuing demand for well-trained statisticians, and the Department has been successful in placing its graduates in positions at universities and research institutes as well as in government, business, industry, and Wall Street.

M.A. in Statistics: On-Campus Program

The M.A. program is designed for students with the goal of enhancing their knowledge of statistical theory and applications. Although some students in the M.A. program are preparing for doctoral study in statistics or other quantitative fields, most are preparing for, or are working in, positions that use statistics, and do not plan on applying to a Ph.D. program. The program has a full time and part time option for domestic students. International students fulfill the program requirements full time.

The M.A. program consists of four required courses and six or more electives. The required courses include basic probability theory and mathematical statistics as well as courses in standard statistical methods. Many of the courses entail practical experience using statistical software. The majority of our full-time students satisfy the minimum requirements for the M.A. degree in three semesters. Required courses are scheduled, as much as possible, for early evening times to accommodate students with full-time employment. Students who complete the free-standing M.A. program and apply to the Ph.D. program will be considered on the same basis as other applicants.

Graduates of the M.A. program have found employment in a variety of areas, including pharmaceutical research, finance, insurance, market research, public health, and government. Professionals with strong interest in broadening their knowledge of applied statistics to prepare for a new career or advance in their current positions are particularly encouraged to apply.  For more information please visit the department website.

M.A. in Statistics: Hybrid Online/On-campus Program

The Department of Statistics offers a program that has select courses online during the first fall semester in its renowned M.A. program. The M.A. Hybrid students are only Hybrid in the first semester of the program and then are completely integrated into the resident program after the first semester. The diploma and degree is identical for initial Hybrid and non-Hybrid entry students.  The Hybrid Online/On-Campus M.A. Program in Statistics consists of two parts:

Part I: Students complete up to four Statistics Courses through Columbia's innovative online learning management system. The first part of the program is designed to establish a deep foundational knowledge of statistical methods, with instruction in modern probability, statistics, and applied statistics, and offers preparation for the more advanced elective courses offered in the on-campus portion of the program. Domestic students may register either part-time or full-time; international students must register full-time.

Part II: Students can complete the remaining elective courses on the Columbia University campus. Domestic students may register either part-time or full-time; international students must register full-time. Regardless of registration type, all remaining classes after the first semester must be completed at the Columbia campus.

Tuition rates are comparable to those for the on-campus M.A. program. While completing the first part of the program, tuition rates will be determined by the number of courses for which a student enrolls. For more information please visit the GSAS Cost of Attendance website.

Additional M.A. Programs

The Department of Statistics also participates in the following GSAS M.A. programs. Click the links below for more information.

M.A. in Mathematics with a Specialization in the Mathematics of Finance

M.A. in Quantitative Methods in the Social Sciences

Special Admissions Requirements: 

Preparation for the Statistics M.A. program should include a thorough knowledge of linear algebra (through the level of MATH V2020 at Columbia) and advanced calculus (through the level of MATH V1201). Experience in theoretical or applied probability and statistics is advantageous. Familiarity with computer programming is also helpful. The GRE exam is required and there is no minimum score. The GMAT will not be accepted as a substitute.

In addition to the requirements listed below, all students must submit one transcript showing courses and grades per school attended, a Statement of Academic Purpose and three letters of recommendation from academic sources. Additionally, fall grades may be required from all Statistics and Statistics-Hybrid M.A. applicants who have not yet received an undergraduate degree.

All international students whose native language is not English or whose undergraduate degree is from an institution in a country whose official language is not English must submit scores of the Test of English as a Foreign Language (TOEFL) or IELTS.

For more information, refer to our Admissions Information and Frequently Asked Questions pages.

Deadline for Fall Admission: 
Friday, April 28, 2017
Resume Requirement: 
Writing Sample: 
GRE General: 
Degree Programs: 
Full Time/Part Time