PhD in BIOSTATISTICS (PhD)OBJECTIVE:Students are trained in the theory and practice of biostatistics. They are given experience in all aspects of data analysis, which includes understanding of the process generating the data, data inspection, the graphical and formal testing of the assumptions of statistical models as well as the more theoretical aspects of hypothesis testing. Graduates from the program will be well suited to work as independent researchers within a university setting, and to take a leadership or supervisory role in university research institutes, government departments, hospitals, pharmaceutical/health corporations, and other health agencies such as cancer research units.
ADMISSION REQUIREMENTS: A Master degree in biostatistics, statistics, biology, computer science, or economics is required, including undergraduate or graduate courses in linear algebra, advanced calculus, probability, and mathematical statistics.
• MA or MSc (or equivalent) with thesis (or relevant research experience)
• A- (80-84%) average or better in a Masters program.
PROGRAM REQUIREMENTSREQUIRED COURSES:• The total number of courses is generally chosen to meet the needs of each student. It is usually between 4 and 6 half courses.
• All students are normally required to take the following three courses listed below. Those students who have completed these requirements at the Master level with at least an A- will be exempted.
• Student who have completed their MSc in this Department may have taken some or all of theses courses already. In this case the program of study will be designed in consultation with the program director at the time of admission.
CHL 5208H Advanced Laboratory in Statistical Design and Analysis
CHL 5209H Survival Analysis I
CHL 5407H Categorical Data Analysis
• Students are generally required to take one to three electives from the following:
CHL5222H Longitudinal Data Analysis
CHL5223H Applied Bayesian Methods
CHL5224H Statistical Genetics
CHL5205H Demography and Vital Statistics I
CHL5406H Prospective Studies and Survival Analysis
STA2209H Lifetime Data Modeling
STA2112H Mathematical Statistics I
STA2212H Mathematical Statistics II
STA3000Y Advanced Theory of Statistics
STA2004Y Design of Experiments
STA2101Y Methods of Applied Statistics I
STA 2542H Linear Models
CHL5401H Introduction to Epidemiology
CHL5402H Epidemiology Methods II
The above requirements apply to all students in general. There will be exceptions. In some situations, the student, in discussion with the Program Director, will be allowed to substitute alternatives for some of the courses in the required list, or be given exemptions based on their previous academic experience.
Students may also find it useful to take other courses from the Department of Public Health Sciences, the Department of Statistics, the Department of Computer Science, or other University departments. It is recommended to consult with the Program Director.
COMPREHENSIVE EXAMINATION: The comprehensive exam is held once a year during the fall term. After at least one complete year (usually after two years) in the program, students must take the exam. The exam consists of a theoretical as well as a practical component. The theoretical component, which covers the areas of probability, mathematical statistics, survival analysis, categorical data analysis, non-parametric methods, statistical epidemiology, and demography, consists of two sit-in examinations of approximately five hours each. In the practical component, the student is given one week to submit a report that summarizes the statistical analysis of at least one dataset.
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