Biostatistics is one of the primary fields in the science and practice of public health, relating statistical information to concrete health issues as they affect human populations.
Biostatisticians often collaborate with public health and clinical professionals to research and analyze problems in a wide range of health sciences, providing the evidence needed to make critical clinical and policy decisions.
Students admitted to the Biostatistics Master of Public Health (MPH) degree program are assigned a faculty advisor who will provide guidance throughout the program. This information serves as a resource to be used by the student and the advisor in planning a program with a specialization in Biostatistics.
There are many institutions that offer degrees in biostatistics, but the faculty in the division of biostatistics at Ohio State makes the program unique. They have created an environment where students feel supported and encouraged while they also push us toward becoming better independent researchers.
--Brittany Bailey, PhD
Program of Study
The MPH-Biostatistics curriculum consists of a minimum of 45 credits organized into five curricular domains:
1. Integrated Foundational curriculum in areas of knowledge basic to public health (12 credits)
2. Courses required for a specialization in biostatistics (12 credits)
3. Elective courses (16 credits)
4. Applied Practice Experience (2 credits minimum)
5. Integrative Learning Experience (3 credits minimum)
For detailed additional information about specific requirements, students are directed to the College of Public Health (CPH) Graduate Student Handbook and to The Ohio State University Graduate School Handbook.
The MPH with specialization in biostatistics is most appropriate for individuals who either have or intend to earn another graduate degree such as an MD or PhD in another field (other individuals are encouraged to consider our MS program). The most important background for biostatistics is good preparation in mathematics. A first course in probability and statistics is desirable, and any applied statistics courses are also helpful. Familiarity with a statistical package (SAS, R, STATA, SPSS, etc.) is also desirable, though not required. Close attention will be paid to grades in quantitative courses of any kind.
For information regarding application materials, test scores and codes, and decision timelines see our frequently asked questions page.