Degree Division
Biostatistics Division
Program Contact
Wendy Lou

degree overview

Graduates from the Biostatistics Division 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

Click here for information regarding the application process.

A Master’s degree in biostatistics, statistics, biology, computer science or economics is required as well as undergraduate or graduate courses in linear algebra, advanced calculus, probability and mathematical statistics.

course Requirements

Course Requirements (5.0 FCE)

  • All students are required to take the courses listed below. Those who have completed similar courses at the Master’s level, and have achieved at least an A-, may be given an exemption, but would be required to replace these courses with electives.
  • Students who have taken their MSc in this department, may have taken some or all of these courses already. In this case their program of study will be designed with consultation of the program director at the time of admission.

Required Courses (4.0 FCE)

CHL5005H: Introduction to Public Health Research 0.5
CHL5208Y: Advanced Laboratory in Statistical Design and Analysis 1.0
CHL5209:H Survival Analysis I 0.5
CHL5210H: Categorical Data Analysis 0.5
CHL5250H: Biostatistics Seminars 0.5
CHL5260H: Doctoral Seminar Series in Biostatistics 0.5
STA2112H: Mathematical Statistics I 0.5
STA2212H: Mathematical Statistics II 0.5

Elective Courses (1.0 FCE)

CHL5222H: Analysis of Correlated Data 0.5
CHL5223H: Applied Bayesian Methods 0.5
CHL5224H: Statistical Genetics 0.5
CHL5225H: Advanced Statistical Methods for Clinical Trials 0.5
CHL5227H: Introduction to Statistical Methods for Clinical Trials 0.5
CHL7001H: Statistical Methods for Genetics and Genomics 0.5
CHL7001H: Statistical Analysis of Health Economic Data 0.5
CHL7001H: Temporal Analysis of Health Policy Intervention 0.5
CHL7001H: Statistical Methods in Data Mining 0.5
CHL7001H: Statistical Analysis of Health Data from Complex Samples 0.5
CHL7001H: Statistical Models on Complex Human Genetic Diseases 0.5
CHL7001H: An Introduction to the Likelihood Paradigm 0.5
CHL7002H: Simulation Methods 0.5
STA2101H: Methods of Applied Statistics I 0.5

Not all courses are offered in every year.  See timetable for current offerings.

Note: Electives may be taken from other departments such as the Department of Statistical Sciences, Department of Computer Science or other University departments, with permission of the Division Head.

Qualifying Examination

PhD students are required to attempt the qualifying exam within the first year of entering the program. The examination, which is usually offered in the late summer, involves both theoretical and practical components, divided into three parts. The theoretical component comprises two in-class exams of 5 hours each, the first (Part I) covering foundations such as probability and mathematical statistics, and the second (Part II) covering biostatistical methodology. The format for the practical component (Part III) is a take-home exam, where the student is given one week to submit a report which summarizes the statistical analysis of at least one dataset.