The Department of Statistics offers an undergraduate major, a M.S. in Statistics, 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 Masters degree in Statistics is oriented towards students who will pursue a career as a practicing statistician in industry, government or academia, and usually takes two years to complete. Required courses for the Masters degree are a two-semester sequence in linear models and design of experiments, a course in statistical consulting, and a course in mathematical statistics. Additional courses include topics such as generalized linear models, nonlinear models, nonparametric analysis, sample surveys, statistical computing, multivariate analysis, and time series analysis. The culmination of the program, the Masters exam, requires the student to analyze two sets of real world data, and to defend the analysis before selected members of the faculty.
The Ph.D. degree program in Statistics prepares students for research and teaching careers in academia or industry, including interdisciplinary research in a wide array of disciplines. Students pursuing a doctoral degree must take courses in several broad areas of statistical methods and theory. Required courses include a course in probability theory, a two-semester sequence in mathematical statistics (based on measure theory), and a course in statistical consulting. The Ph.D. qualifying examination is primarily based on the mathematical statistics and probability theory courses. The major requirement for the degree is to conduct original research in some area of statistics and to present the research in a dissertation. Most students complete the Ph.D. in four to five years.
Upon completion of either the M.S. or Ph.D. degree, students usually find that their sound background of theory and application makes them very desirable employees, and have a wide range of exciting job opportunities to choose from.
Web: Graduate School Page on Statistics
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.
Department of Biostatistics and Medical Informatics K6/446 Clinical Science Center 600 Highland Avenue Madison, WI 53792
Telephone: (608) 263-1706 Fax: (608) 265-5579
Graduate School Page on Biostatistics Named Option
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.
Web: Biometry MS Information
Graduate School Page on Biometry