Biostatistics
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Introduction
Degree Programs
Admissions
Financial Support
Opportunities for Graduates
Further Information
Biostatistics is a discipline concerned with the development of statistical principles and methods and their application to problems in the medical, biological, and health sciences. A broad knowledge of biology and a solid understanding of statistics are fundamental to successful training in biostatistics. The integration of knowledge from subject matter areas with the theory and practice of statistical methods makes biostatistics a coherent field of study.
The Interdepartmental Group in Biostatistics at the University of California, Berkeley, offers graduate programs leading to the M.A. and Ph.D. degrees. These programs are appropriate for the student who has either a mathematical or statistical background with a major interest in the biomedical sciences or a degree in the biological sciences with a major interest in mathematics and statistics. The curriculum is offered principally by statistics and biostatistics faculty drawn from both the Department of Statistics and the School of Public Health.
An M.A. degree candidate enrolls for four semesters, satisfies certain unit requirements with courses selected from biostatistics and statistics, public health, and biology, and completes an oral comprehensive examination.
The Ph.D. degree program includes four to six semesters of course work selected from biostatistics, statistics, and other areas of interest. Candidates complete an oral qualifying examination and prepare a dissertation.
Topics for study are selected from biostatistics and statistics, public health, biology and computer science. Courses include traditional topics as well as recent advances in biostatistics and statistics. Since biostatistics plays a role in a variety of areas such as epidemiology, genetics, and environmental health, courses in these areas are also core to both the M.A. and Ph.D. programs.
M.A. degree candidates in biostatistics will be well-versed in several areas at the completion of the program:
- Fundamental statistical methods of analysis of data, including statistical estimation, hypothesis testing, regression analysis, analysis of variance and longitudinal data.
- Algorithms and computer applications.
- Analysis of multivariate data—categorical and continuous—with particular emphasis on epidemiology.
- Interpretation of survival analysis data and issues, including knowledge of life table methodology, competing causes of death, medical follow-up studies, parametric models and nonparametric methods.
- Computational biology methods including gene mapping, microarray data analysis and other topics in genomics.
- Methods of analysis using vital and health statistics, census data, rates and adjusted rates.
Those completing doctorates will acquire deeper understanding of these subject areas. Since doctoral graduates often assume academic careers in research and teaching, a high degree of mastery in research design, theory, methodology and data analysis is expected as well as the ability to communicate and present research findings in a clear, understandable manner.
With recent developments in genetics and molecular biology, and the impetus of the genome projects, interactions between the biological and mathematical sciences are crucial. Analysis and interpretation of large and complex genomic datasets requires interdisciplinary expertise and collaboration of biologists, statisticians, and computer scientists. In response to these new interdisciplinary challenges, a formal academic structure—The Designated emphasis in Computational and Genomic Biology—has been created to link and coordinate activities. This structure systematizes graduate training, and provides students with a solid foundation in the different facets of genomic research.
Students in the Group in Biostatistics have opportunity to choose the designated emphasis as an adjunct to Ph.D. degree in biostatistics.
For information on this option, visit the Computational Biology web site at http://computationalbiology.berkeley.edu.
The Group in Biostatistics welcomes applicants from a variety of disciplines. Acceptable candidates for the M.A. degree program have completed at least a year or two of calculus and a course in linear algebra. Those applying for the Ph.D. should possess a strong quantitative background exceeding the minimum requirements for admission for the M.A. Three letters of recommendation, a statement of purpose and GRE scores (general test) must be submitted in support of an application. All applicants, regardless of citizenship, must take the GRE. Applicants from non-English speaking countries must pass the TOEFL with a score of 570 (230 on the computer-based test).
Applicants must also meet the School's admissions requirements to be admitted to the program.
University Fellowships, teaching and research positions are available to qualified students. A limited number of merit-based tuition and fee awards are available through the Group in Biostatistics.
Graduates in biostatistics find career opportunities in health departments, government agencies, and private industry as well as teaching/research positions in colleges and universities.
To learn more about biostatistics degree programs, visit the web site http://www.stat.berkeley.edu/biostat or send an e-mail to biostat@berkeley.edu.