Program Overview
The Master’s program in Biostatistics is an applied one-year program intended for quantitative students seeking training in applied biostatistics. The program emphasizes applications and understanding of statistical concepts rather than theoretical and mathematical principles. The program is meant to be a degree to provide students with a necessary background for applying good biostatistical practices in real-world settings. Students will gain practical skills that can be applied immediately to a variety of data settings, which includes, but is not limited to, the biological life sciences, public health, medical studies, health services research.
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Academic and Application Information
Below is the academic and application information on the M.S. in Biostatistics program. If you are considering a career in Biostatistics or in applying to the program, please visit Why Study Biostatistics and Student and Alumni Spotlights for additional information.
Competencies
The MS in Biostatistics degree is accredited by the Council on Education for Public Health (CEPH).
Upon completion of the MS in Biostatistics degree, all graduates will be able to:
- Competencies:
| Apply epidemiologic and statistical methods to the measurement and study of population health and the prevention of infectious and chronic disease |
| Describe concepts in probability theory, random variation and commonly used statistical distribution and mathematical statistics |
| Develop sample size and power calculations for different study designs including those from clinical trials and observational studies |
| Perform a variety of basic and advanced statistical analyses (estimation and inference) including ANOVA, univariate and multiple regression models, generalized linear modeling, multivariate analysis, survival analysis, designs of experiments, various new techniques from statistical learning theory, analyze longitudinal data |
| Apply quantitative and reasoning skills as well as content-area knowledge to analyze data from epidemiological, clinical, observational and experimental studies |
| Interpret results from explanatory and descriptive data analysis and advanced statistical analyses to draw relevant conclusions from data |
| Develop a high level of competency in statistical programming both in R and SAS for both managing and analyzing data |
| Communicate effectively by producing summary reports, statistical analysis sections of papers, graphical summaries and tabular summaries of data |
| Gain successful practical experience in statistical consulting, including interaction with research faculty in the health sciences |
- Average Program Duration: 1 year
- Total required credits: 33 credits
The Curriculum
The degree consists of 33 credits covering introductory probability, biostatistics, introductory epidemiology and public health, computing, clinical trials, introductory survival analysis, and introductory mathematical statistics. Enrichment will be provided by a statistical practicum and a seminar course. Prerequisites include introductory calculus, introductory linear algebra, and introductory computing.
- Core Courses (33 credits)
1 Note that BST 650 is taken for 1 credit in the fall and 1 credit in the spring for a total of 2 credits.
Curriculum information and course descriptions can be found here.
For the program application, click below.
