Interdisciplinary PhD Program in Biostatistics

Biostatistics is one of the fundamental specializations in the science and practice of public health, relating statistical information to concrete health issues -- especially those affecting human populations. The information provided by biostatisticians is central to the design of interventions and the development of public health policy and priorities.

Our biostatistics faculty include nationally known experts on health metrics. Our experts collaborate with colleagues throughout the OSU Health Sciences campus as well as peers across the nation. Current research by the biostatistics faculty includes survival analysis, logistical regression, cancer statistics, genomics, proteomics, and environmental and occupational risk assessment. These partnerships result in well-designed studies and properly analyzed data.

The doctoral program in Biostatistics presupposes a mathematical background that includes linear algebra and advanced calculus.The PhD degree requires a significant program of study and research that qualifies the recipient to work independently and contribute to the advancement of the field of knowledge. The emphasis is on mastery of the field and particularly on the acquisition of research skills as a basis for original work.  After declaring a specialization during the second year of study, students in the Biostatistics PhD program who choose the Public Health specialization will be assigned faculty advisors from the Biostatistics faculty.

Application materials and program information can be found at

For additional information about general PhD requirements, students are directed to the College of Public Health (CPH) Graduate Student Handbook and to the Ohio State University Graduate School Handbook.

Recommended Preparation

The most important background for biostatistics is good preparation in mathematics, especially courses in calculus and linear algebra. A first course in probability and statistics is desirable, and any applied statistics courses will be helpful. Familiarity with a statistical package (such as SAS, R, Splus, Stata, SPSS) is also desirable. Close attention will be paid to grades in quantitative courses of any kind. Verbal and quantitative GRE scores should individually be 600 or above, and many students will score well above that, especially on the quantitative portion.

For information regarding application materials, test scores and codes, and decision timelines see our frequently asked questions page.

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