MS in Statistics


Students working with computers in a statistics class


The Master of Science in Statistics program is ideal for students who are preparing for professional positions or doctoral programs in statistics and other quantitative fields.

Thesis and non-thesis options are available, and students may enroll full time or part time. Use of statistical software packages, available in all university computer labs, is required for most courses.

Application Deadlines:

  • April 1 (fall semester)
  • February 1 (applicants seeking funding)
  • October 1 (spring semester)




Graduate Virtual Open House



Graduate Virtual Open House: October 18–28

Registration is open for the Columbian College of Arts and Sciences (CCAS) Graduate Virtual Open House! The online event includes program-specific information sessions and opportunities to engage with current graduate students, faculty and our admissions team.

The Statistics Department is hosting an information session for prospective graduate students on Tuesday, October 19 at 9 a.m. EDT. 


Program of Study

The MS program offers a combination of mathematical statistics, applied statistics and statistical computing tailored to each student. Before signing up for classes, all new students must meet with the MS program director to design an individualized program of study. The program of study should take into account the student's strengths and deficiencies, as judged from transcripts and interviews. It is recommended that students continue to seek advice throughout their time in the program.

Students must also maintain a minimum cumulative grade point average of B (3.0) in all coursework.


Credit Transfers

MS in Statistics students may transfer up to two approved courses (six credits) taken outside the Statistics Department for credit, but they must be in related fields (e.g., economics, management and finance, computer science, engineering, mathematics or public health). To begin the transfer process, students should talk to their advisors and complete the Graduate Student Transfer Credit Request Form available on the CCAS website. The CCAS Master’s Student Handbook also provides additional guidance and information on degree requirements.

CSCI 6212: Design & Analysis of Algorithms 

CSCI 6364: Database Management Systems

CSCI 6442: Database Systems II 

CSCI 6907: Big Data & Analytics 

ECON 8375: Econometrics I 

ECON 8377: Econometrics II 

FINA 6223: Investment Analysis & Portfolio Mgmt 

MATH 6201: Real Analysis I 

MATH 6202: Real Analysis II

MATH 6230: Complex Analysis 

MATH 6441: Introduction to Financial Math 

MATH 6620: Graph Theory 

MKTG 6243: Marketing Research 

PUBH 6002: Biostatistical Applications for Public Health 

DATS 6102: Introduction to Data Science 

DATS 6102: Data Warehousing

Rolling Credits Into PhD Option

If desired, a student may complete the MS in Statistics program prior to admission to the PhD program, in which case no more than 24 credit hours from the MS degree may be applied to the PhD requirements. In this instance, the student will be required to take a minimum of 27 additional credit hours of coursework. The distribution of these courses between statistics and public health would depend on the nature of the master's degree and whether the transferred credit hours would be used to defray statistics or public health coursework. Full information is available in the online Graduate Admissions Application. 


Optional Thesis

All candidates for the MS in Statistics complete at least 30 units of graduate credit approved for the department. For students who wish to complete a thesis, the department can approve a program of study consisting of 24 credit hours of coursework plus a thesis. 

  • Non-thesis option: Students complete six credits in required courses and 24 credits in elective courses for a total of 30 credits.
  • Thesis option: Students complete six credits in required courses (STAT 6998-6999), six thesis credits and 18 credits in elective courses, also totaling 30 credits.

All master’s theses must be supervised by a director plus one reader. It is up to the student to find a topic and a thesis advisor. Ask your academic advisor for guidance. Only after you find a thesis advisor you should register for STAT 6998 and STAT 6999 over two semesters.

"I have benefited from the program in many ways. I especially appreciate the program accommodating those like me who have a daytime job, since all master’s-level courses are offered in the afternoon."

Wenliang Yao

MS ’08, Statistics; PhD ’13, Biostatistics
Principal Statistician, MedImmune

Course Requirements

Prerequisites: These courses (or equivalents) are prerequisites for admission consideration and MUST appear on your transcript. Submit your MS in Statistics program application only after you have completed all of the required courses.

  • MATH 1231: Single-Variable Calculus I (3 credits)
  • MATH 1232: Single-Variable Calculus II (3 credits)
  • STAT 2118: Regression Analysis (3 credits)

General prerequisite: coursework in multivariate calculus, matrix theory, and at least two undergraduate statistics courses.

The following requirements must be fulfilled:

The general requirements stated under Columbian College of Arts and Sciences, Graduate Programs.

30 credits. For non-thesis option—6 credits in required courses and 24 credits in elective courses. For thesis option—12 credits in required courses, including 6 credits in thesis, and 18 credits in elective courses. Students must have departmental approval to pursue the thesis option.

STAT 6201Mathematical Statistics I
STAT 6202Mathematical Statistics II
For students pursuing the thesis option:
STAT 6999Thesis Research (taken twice for total of 6 credits)
For non-thesis option: 24 credits in electives, at least 18 of which must be in STAT courses. For thesis option: 18 credits in electives, at least 12 of which must be in STAT courses.
Elective courses outside statistics may be taken in related fields, such as economics, mathematics, finance, management, computer science, engineering, public health, and data science.