Masters of Science in Biostatistics – Overview

Program Director: Mendel Singer, PhD MPH

The CWRU MS Biostatistics program is 31 credits and is designed to be able to be completed in 1 year, covering the fall/spring/summer semesters. The final, summer semester consists of an internship or practicum that can be done locally in Cleveland or elsewhere, as the required summer course is offered online. However, students may choose to do the program at a slower or part-time pace.

Students choose one of four tracks: 

  • Biostatistics
  • Genomics and Bioinformatics
  • Health Care Analytics
  • Social and Behavioral Science


Biostatistics Track

Track Leader: Abdus Sattar, PhD

The biostatistics-track students will receive a carefully designed balanced training in biostatistical theories and methods. This track student will gain mastery of basic probability theory and statistical inference, learn the methods of longitudinal analysis, and still have the flexibility to choose an elective from the following advanced courses: A) Data mining, B) Multivariate Analysis and Data Mining, C) Causal Inference, and D) Statistical Computing. The didactic methods and theory, and hands on analytical training would lead to either pursue an advanced relevant degree and/or work as a master’s level bio/statistician in various settings, e.g. academia, (pharmaceutical) industry, government agencies.

Track-Required Courses:

  • Introduction to Statistical Theory (PQHS 480)
  • Longitudinal Data Analysis (PQHS 459)
  • Survival Analysis (PQHS 435)
  • One of the following courses:
    • Machine Learning and Data Mining (PQHS 471)
    • Multivariate Analysis and Data Mining. (STAT 426)


Genomics and Bioinformatics

Track Leader: Chun Li, PhD

Students will be trained to work in genomics and bioinformatics areas. In addition to the basics in biostatistics, they will learn the designs, methods, techniques, and tools that are commonly used in genetic epidemiology, statistical genomics, and bioinformatics research.  Target job positions are analyst, statistician and bioinformatition in a genomics or genetic epidemiology research team in a research institute or large pharmaceutical company.

Track-Required Courses:

  • Bioinformatics and Genetic Epidemiology (PQHS 451)
  • Sequencing (PQHS 452)
  • Advanced Methods in Genetic Epidemiology (PQHS 457)
  • Machine Learning and Data Mining (PQHS 471)


Health Care Analytics

Track Leader: Thomas Love, PhD

Biostatistics is a vital part of clinical research, which includes both observational studies and randomized clinical trials. Modern clinical, or patient, research takes advantage of innovative methodologies for the design and analysis of such studies to increase the likelihood of success and minimize patient burden and the use of scarce resources. Clinical research biostatisticians work as part of multi-disciplinary teams with clinical and statistical investigators to develop and execute study designs and analysis plans with scientific rigor, and in support of regulatory requirements by sanctioning bodies and funding agencies. Principal roles include the design, analysis, coordination and reporting of observational and trial-based clinical research studies. Most of a clinical research biostatistician’s work is dedicated to evaluating, executing and reporting on well-designed studies so as to help investigators meet their scientific objectives. Related job titles include biostatistician, lead, senior or principal biostatistician, consulting statistician, statistical researcher, statistical programmer, clinical informatition and clinical research manager. Such positions require strong written and verbal communication skills, and the ability to work as part of a team with subject matter experts on protocol development and statistical reporting. Biostatisticians completing the Clinical Research track will be well-positioned to apply for positions in industry, academia (including teaching hospitals) and government. Recent graduates of similar programs have found excellent positions with pharmaceutical companies, university and health system-based research groups, and within various health industries.

Track-Required Courses:

  • Survival Analysis (PQHS 435)
  • Large Health Care Databases and Electronic Health Records (PQHS 515)
  • Two of the following courses:
    • Longitudinal Data Analysis (PQHS 459)
    • Observational Studies (PQHS 500)
    • Clinical Trials (PQHS 450)
    • Machine Learning and Data Mining (PQHS 471)


Social and Behavioral Science

Track Leader: Arin Connel, PhD

Students will be trained to work as analysts and research assistants in the social and behavioral sciences, including anthropology, sociology, psychology and social work. Students will be trained in the most common study designs and analytic methods in these application areas. This track is intended for students whose undergraduate work involved a major or minor in one of the social and behavioral sciences. It was created to serve the needs of social and behavioral science researchers who need research analysts trained in statistics, but with an understanding of their field and familiarity with qualitative and mixed methods as well. Target job positions are in academia, government and research institutes.

Track-Required Courses:

  • Longitudinal Data Analysis (PQHS 459)
  • Measurement of Behavior (PSCL 412)
  • Structural Equation Modeling (NURS 632)
  • Qualitative and Mixed Methods (MPHP 482)