Overview of Statistics Degrees
The Department of Statistics offers both a M.S. and a Ph.D. in Statistics and several joint degrees with other departments. The M.S. degree program is distinct from the Ph.D. degree program.
The Department of Statistics in collaboration with the Department of Biostatistics and Medical Informatics in the Medical School offers both a M.S. and a Ph.D. in Statistics with emphasis in Biostatistics. In addition to satisfying the requirements for a degree in statistics, Master's and Ph.D. students are required to take two courses in biostatistics exploring topics in clinical trials and epidemiological studies. Ph.D. students are required to take a course in survival analysis methodology. Additional courses in design, sample survey, nonparametrics, and categorical data analysis are also recommended. A career in biostatistics offers exciting and challenging opportunities in clinical research, genetics, drug testing, and experimental design. Biostatisticians find themselves in demand in academia, government, and the private sector.
A Master's program in biometry focuses on the application of statistics to agriculture, ecology, and nonmedical biology. Knowledge of statistics and an understanding of biological principles are necessary for proficiency in biometry. Courses for this degree include material in experimental design, modeling, nonparametric methods and categorical data analysis, as well as their applications to the problems in the biosciences. Students are required to complete a course in consulting and to write a paper representing an original contribution to biometry. Such a contribution may involve a thorough analysis of an interesting biological data set, or the evaluation of an experimental design used in some scientific discipline. Upon completion of the course work, an oral examination will be conducted by selected members of the faculty. We anticipate that this program will appeal mainly to students who wish to pursue a career in the biological sciences and who want to augment that with a solid quantitative background.