Biostatistics involves the development and application of statistical methods to scientific research in areas such as medicine, epidemiology, environmental health, genetics, and ecology. Biostatisticians play key roles in designing studies—from helping to formulate the questions that can be answered by data collection to the decisions on how best to collect the data—and in analyzing the resulting data. They also develop new statistical methods for such data. Students will take courses, and may do research, on topics such as mathematical statistics, statistical methods for epidemiology, generalized linear models, survival analysis, longitudinal data, and clinical trials. The Department of Epidemiology, Biostatistics, and Occupational Health has one of the largest concentrations of Ph.D.-level statisticians in any Canadian Faculty of Medicine.
|Master of Science (M.Sc.); Biostatistics (Thesis) (48 credits)|
|M.Sc. thesis students study a foundational set of courses, and write a thesis on a topic of their choice. Thesis students should have a strong interest in research. These students are well-placed to either continue in a Ph.D. program or to work in academic research in statistics or medicine; they will also have relevant qualifications for the pharmaceutical industry and government.|
|Master of Science (M.Sc.); Biostatistics (Non-Thesis) (48 credits)|
|The M.Sc. non-thesis program is designed to expose students to a wide range of topics including statistical methods for epidemiology, generalized linear models, survival analysis, longitudinal data, and clinical trials. Skills in data analysis, statistical consulting, communication, and report writing are emphasized, and students graduate ready to work in the pharmaceutical and biotechnology industries, in government, or in academic medical research.|
|Doctor of Philosophy (Ph.D.); Biostatistics|
|Applicants should hold a master’s degree in mathematics or statistics or its equivalent. Mastery of calculus, linear algebra, real analysis, and mathematical statistics is essential. Exposure to data analysis is an asset. Exceptional students without a master’s degree will be considered for admission, starting with a Qualifying year. Ph.D. students typically work on development of statistical methods, and can specialize in statistical methods for epidemiology, generalized linear models, Bayesian methods, survival analysis, longitudinal data, causal inference, and clinical trials. Skills in data analysis, statistical consulting, and report writing are emphasized. Ph.D. graduates typically work as faculty in universities, in research institutes, in government, or in the pharmaceutical industry.|