MS in Biostatistics


A graduate stats student working at a computer in a classroom


In the Master of Science in Biostatistics program, students develop the skills and methods necessary to thrive in the biological, biomedical and health services sciences. Coursework includes statistics, mathematics and public health as well as a comprehensive examination.

The biostatistics program is jointly administered by the Department of Statistics and the Department of Biostatistics and Bioinformatics in the GW Milken Institute School of Public Health (SPH). 

Application Deadlines: 

We are not accepting new applications for Fall 2022.


Student Learning Outcomes

  • Understand the theory and principles behind the statistical methods most commonly used in biomedical research (contingency tables, survival analysis, mixed models and missing data)
  • Learn and apply the underlying principles and methods to design, plan and conduct biomedical studies
  • Provide biostatistical advice as a member of a team engaged in a biomedical research project; this expertise includes the manipulation and analysis of data



Middle States Commission on Higher Education (MSACHE) logo


This degree program is accredited by the Middle States Commission on Higher Education through the Columbian College of Arts and Sciences and by the Council on Education for Public Health through the SPH regulations.



MS Transfer Credits

Students may complete the GW Master of Science in Biostatistics program prior to admission to the PhD degree program. In this case, no more than 24 credit hours from the MS degree may be applied toward the PhD coursework 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. Students should consult their academic advisor for more details on this option.


Course Requirements

The following requirements must be fulfilled: 33 credits, including 18 credits in core statistics courses, 7 credits in core public health courses, 6 credits in elective courses, and 2 credits in consulting.

Admission Considerations

The courses listed below (or equivalents) are prerequisites for admission consideration and must appear on the student's transcript. Students may apply to the program only after they have fulfilled this requirement: 

MATH 1231Single-Variable Calculus I
MATH 1232Single-Variable Calculus II
STAT 2118Regression Analysis

Applicants lacking the courses listed below (or equivalents) are considered for admission; however, if admitted, the student is required to complete these courses within two semesters of matriculation in the program. Credit earned in these courses does not count toward the 33 credits required for the degree and grades earned are not reflected in the overall grade-point average.

MATH 2184Linear Algebra I
MATH 2233Multivariable Calculus
One of the following:
PUBH 6853Use of Statistical Packages for Data Management and Data Analysis *
STAT 2183Intermediate Statistics Lab/Packages

*Previously PUBH 6249.

Degree Requirements

Required statistics courses
PUBH 6266Biostatistical Methods
or PUBH 8877 Generalized Linear Models in Biostatistics
STAT 6201Mathematical Statistics I
STAT 6202Mathematical Statistics II
STAT 6210Data Analysis
STAT 6227Survival Analysis
STAT 6255Clinical Trials
or PUBH 6866 Principles of Clinical Trials
Public health courses
PUBH 6003Principles and Practices of Epidemiology
2 credits (two courses) selected from the following:
PUBH 6262Introduction to Geographic Information Systems
PUBH 6263Advanced GIS
PUBH 6850Introduction to SAS for Public Health Research
PUBH 6851Introduction to R for Public Health Research
PUBH 6852Introduction to Python for Public Health Research
PUBH 6856Advanced SAS for Public Health Research
2 additional credits in any PUBH course(s) in the 6800 range.
Approved Electives
6 credits in elective courses selected from the following:
PUBH 6854Applied Computing in Health Data Science
PUBH 6859High Performance and Cloud Computing
PUBH 6860Principles of Bioinformatics
PUBH 6861Public Health Genomics
PUBH 6862Applied Linear Regression Analysis for Public Health Research
PUBH 6863Applied Meta-Analysis
PUBH 6865Applied Categorical Data Analysis
PUBH 6879Propensity Score Methods for Causal Inference in Observational Studies
PUBH 6884Bioinformatics Algorithms and Data Structures
PUBH 6886Statistical and Machine Learning for Public Health Research
PUBH 6887Applied Longitudinal Data Analysis for Public Health Research
STAT 3187Introduction to Sampling
STAT 4181Applied Time Series Analysis
STAT 4188Nonparametric Statistics Inference
STAT 6197Fundamentals of SAS Programming for Data Management
STAT 6214Applied Linear Models
STAT 6215Applied Multivariate Analysis I
STAT 6216Applied Multivariate Analysis II
STAT 6217Design of Experiments
STAT 6223Bayesian Statistics: Theory and Applications
STAT 6225Longitudinal Data Analysis
STAT 6231Categorical Data Analysis
STAT 6240Statistical Data Mining
STAT 6242Modern Regression Analysis
STAT 6252Statistical Methods in Bioinformatics and Computational Biology
STAT 6254Statistical Genetics
STAT 6287Sample Surveys
STAT 6289Topics in Statistics
STAT 8226Advanced Biostatistical Methods
STAT 8265Multivariate Analysis
STAT 8273Stochastic Processes I
STAT 8281Advanced Time Series Analysis
STAT 8288Topics in Sample Surveys
PUBH 6883Biostatistics Consulting Practicum
PUBH 6869Principles of Biostatistical Consulting
Master's Comprehensive Examination
Students must successfully complete a master's comprehensive examination, a written examination in the field of biostatistics and is based on the material covered in PUBH 6266 or PUBH 8877. The examination is administered by the faculty of the Department of Biostatistics and Bioinformatics in the Milken Institute School of Public Health.