Type of Degree

M.S., Accelerated Entry into Master's Program

School or College

College of Engineering and Mathematical Sciences

Area of Study

Science, technology, engineering and mathematics

Program Format

On-campus, Full-time

Program Overview

Researchers view data collected by wearable technology

This program offers a concentration in biostatistics leading to the M.S. degree.

Emphasis is placed on learning how to design studies and perform data analysis as the statistician in a research team. The curriculum takes full advantage of courses taught in the Statistics Program and includes potential experience in a variety of health, biomedical, natural resource and other research projects in the College of Medicine or other departments of UVM. This experience is designed to provide candidates with opportunities to use their academic training and work experience in defining research problems, formulating rational methods of inquiry, and gathering, analyzing, and interpreting data.

The program has close ties with the College of Medicine's Department of Medical Biostatistics and Bioinformatics, whose research activities cover the full range of studies that take place within an academic medicine environment. These include population-based health surveys of various types and evaluations of health promotion programs and professional education activities, such as community intervention studies to prevent smoking and to promote breast cancer screening. They also include clinical studies of many different interventions, bioengineering experiment design and measurement studies, statistical genetics, as well as data from other preclinical, clinical, and epidemiological studies.

Opportunities are also available for biostatistical research related to problems in agriculture and the life sciences, as well as natural resources and the environment. Opportunities could include multivariate or spatial data analyses for ongoing wildlife and water quality studies, for example. Students can gain research and consulting experience through the research requirement: a research project (STAT 6810) or a thesis (STAT 6391). Other opportunities for experience may arise through involvement in the Statistical Consulting Clinic (STAT 6850). (See also Statistics Program and Statistical Consulting Clinic descriptions.)

Curriculum

The department offers both a thesis option and a non-thesis option within the MS degree in Biostatistics.

Under both plans, students must have or acquire a knowledge of the material in Biostatistics 211, attend the regular colloquium series and participate in the Statistics Student Association Journal Club as part of their training. The comprehensive examination covers knowledge acquired in the core courses of the program.

Thesis Option

This is a 30-hour program requiring 24 semester-hours of coursework. The program must include:

  • Biostatistics 200, 221, 223, 231, 251,261, 360;
  • plus 6 semester hours of approved thesis research (Bios 391).

Non-Thesis Option

This is a 30-hour program requiring 27 semester-hours of coursework. The program must include:

  • Biostatistics 200, 221, 223, 231, 251, 261, 360
  • Other 200/300 level statistics courses (except 211, 241, 381), or (if approved) other courses in mathematics, quantitative methods, or specialized fields of application
  • Plus 3 semester hours of either approved statistical research (Stat 381) or statistical consulting (Stat 385)

Under the non-thesis option, students will be expected to take major responsibility for a comprehensive data analysis or methodological research project, and are encouraged to present the results from the project.

Graduate-level courses in Biostatistics

Admissions

The following are required for admission to our graduate programs in statistics or biostatistics.

  • A baccalaureate degree
  • Three semesters of calculus, through multivariable calculus
  • (UVM MATH 1234, MATH 1248, and MATH 2248 or equivalent)
  • A course in matrix methods (UVM MATH 2544 or equivalent)
  • At least one course in statistics (such as UVM  STAT 1410). Certainly more background, in terms of formal coursework in statistics and/or experience with data analysis, is highly desirable.

It is possible to be admitted to our programs (but not to candidacy) if some of the course pre-requisites have not been satisfied. All pre-requisites must be completed prior to receiving the MS degree.

For international students taking the TOEFL (Test of English as a Foreign Language), scores of at least 90 are required for admission and at least 100 for a Graduate Teaching Assistantship. The Institution Code for test scores for UVM is 3920.

All applications must be completed online. For further information visit the Graduate College.

Applications will require three letters of recommendation, college transcripts, and TOEFL scores for those whose native language is not English.

Applicants whose files are complete by January 15 receive full consideration for admission and for financial support starting in the Fall Semester. The deadline for all other applicants is April 1. Typically, we don't consider admissions for the Spring Semester, although we do sometimes make an exception for highly qualified applicants that need to complete some of the prerequisites. Financial support is not available in such cases.

Apply online

Outcomes

Graduating Students from the Biostatistics (M.S.) program should be able to:

  • Design: Critically appraise strengths and weaknesses of study designs and identify designs that are appropriate for addressing specific research questions.
  • Data analysis: Demonstrate statistical reasoning, formulate problems in statistical terms, use exploratory and graphical data analysis techniques, and use a variety of formal inference procedures.
  • Theory: Understand important theoretical results and their role in answering inferential questions.
  • Computing: Demonstrate proficiency in use and application of standard statistical software for data management and algorithmic problem-solving.
  • Communication: Demonstrate strong communication skills to effectively collaborate as part of interdisciplinary teams, including the ability to communicate the results of a statistical analysis through oral and written reports to non-experts.