MS in Statistics

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)

Join the Graduate Programs Virtual Open House: October 17–27

Registration is open for the Columbian College of Arts and Sciences 2023 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 Wednesday, Oct. 18 at 4:00 p.m. EDT. 

Registration and Details

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.

Curriculum

The MS program offers a combination of theoretical, applied and computational statistics courses tailored for each student. The MS program requires 30 credits, no qualifying exam; and students can select from the following tracks or courses based on their interests in consultation with faculty advisors.

Biostatistics Track: Data Analysis, Applied Linear Models, Longitudinal Data Analysis, Survival Analysis, Categorical Data Analysis, Statistical Methods in Bioinformatics and Computational Biology, Clinical Trials, Causal Inference, Network Analysis

Computational Track: Fundamentals of SAS Programming for Data Management, Methods of Statistical Computing, Statistical Data Mining, Modern Regression Analysis, Statistical Methods in Bioinformatics and Computational Biology, Statistical Machine Learning, Statistical Deep Learning, Natural Language Processing

Applied Track: Data Analysis, Applied Linear Models, Applied Multivariate Analysis, Design of Experiments, Bayesian Statistics, Longitudinal Data Analysis, Categorical Data Analysis, Modern Regression Analysis, Statistical Consulting, Legal Statistics, Sample Surveys, Causal Inference, Fundamentals of SAS Programming for Data Management

Theoretical Track: Mathematical Statistics, Linear Models, Bayesian Statistics, Probability, Distribution Theory, Advanced Probability, Nonparametric Inference, Advanced Statistical Theory, Multivariate Analysis, Stochastic Processes

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. 

Pre-approved Courses Outside the Department

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

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.

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)