Biostatistics (BS)
Biostatistics is the application of statistical methods to medicine and public health. Biostatisticians generally work as part of a research team, and are responsible for the design of studies, the analysis of the resulting data, and the communication of the results. In recent years biostatistics has become an indispensable tool for improving public health and reducing illness and the demand for those trained in the field is great and growing. The major in Biostatistics includes a foundation in mathematics, a core of applied and theoretical statistics courses, and relevant biology and computing courses. Biostatistics provides a deep and wide foundation in quantitative methods that can form the basis for a career in numerous fields. A Biostatistics major can usefully be combined with a major in any health science or indeed with a major in any field which makes extensive use of quantitative methods.
Program Requirements:
The required courses for the Biostatistics major are
CS 112 followed by MATH 4101 (Programming in SAS at Emmanuel College.)
In addition, students must take two biology courses:
one from
and the other from a 200- or 300- level biology course.
We recommend but do not insist that students take PH 201 Epidemiology. Finally, at least four semester hours of independent learning (for students entering prior to September 2014) or the Capstone (for students entering September 2014 or later) must be completed in Biostatistics. MATH 390 may be used to satisfy the Capstone requirement. It is Departmental policy that courses required for a major or minor should not be taken pass/fail.
The Student Learning Outcomes for the Biostatistics major are: Students will be able to:
- Select from, use and interpret results of, descriptive statistical methods effectively;
- Demonstrate an understanding of the central concepts of modern statistical theory and their probabilistic foundation;
- Select from, use, and interpret results of, the principal methods of statistical inference and design;
- Communicate the results of statistical analyses accurately and effectively;
- Make appropriate use of statistical software;
- Read and learn new statistical procedures independently