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The MSc Biostatistics Course-only option meets the needs of those who intend to pursue a PhD in biostatistics and those who plan to join the workforce after completing the MSc.

Students registered in this option require 5.0 FCE (equivalent to 10 half courses) to graduate. The program includes both mandatory (4.0 FCE) and elective (1.0 FCE) courses as outlined below.

Program Requirements

Required Courses: (4.0 FCE) FCE
CHL5004H: Introduction to Public Health Science 0.5
CHL5207Y: Laboratory in Statistical Design and Analysis 1.0
CHL5209H: Survival Analysis I 0.5
CHL5210H: Categorical Data Analysis 0.5
CHL5250H: Biostatistics Seminars 0.5

Plus one of either:

CHL5226H: Mathematical Foundations of Biostatistics
or
STA2112H: Mathematical Statistics I

0.5

Plus one of either:

CHL5223H: Applied Bayesian Methods
or
STA2212H: Mathematical Statistics II

0.5

Elective Courses

Effective September 1, 2019 students registered in the MSc Biostatistics program will only be allowed to choose elective courses offered by the Division of Biostatistics, Department of Public Health Sciences. Elective courses from other departments (e.g. Statistical Sciences, Computer Science) are allowed, with approval from the Program Director, but these courses will not count towards your MSc degree requirements.  See list of acceptable electives below:

Elective Courses (1.0 FCE) FCE
CHL5212H: Predictive Modelling in the Health Sciences 0.25
CHL5213H: Methods of Analysis of Microbiome Data 0.25
CHL5222H: Analysis of Correlated Data 0.5
CHL5225H: Advanced Statistical Methods for Clinical Trials 0.5
CHL5227H: Introduction to Statistical Methods for Clinical Trials 0.5
CHL5229H: Modern Biostatistics and Statistical Learning 0.5
CHL5230H: Applied Machine Learning for Health Data 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 Analysis of Health Data from Complex Samples 0.5
CHL7001H: Statistical Models on Complex Human Genetic Diseases 0.5
CHL7002H: Simulation Methods 0.5
CHL8001H: An Introduction to the Likelihood Paradigm 0.25
CHL8001H: Introduction to Joint Modeling in Health Research 0.25

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

The Practicum: CHL5207Y Laboratory in Statistical Design and Analysis

Format

This is a full year course with the following format:  i) a weekly 2-hour lecture and ii) a 4-hour per week practicum. Weekly lectures focus on design issues in term 1 and analysis issues in term 2. The practicum occurs at the supervisor’s employment site. To that end, students will be encouraged to integrate themselves as much as possible into their practicum setting.

Objectives

The main goal of the lecture series is to introduce the student to common statistical design and analysis techniques encountered by the practicing biostatistician/data scientist. The main goal of the practicum is to provide the student with hands-on experience with design and analysis issues encountered by applied statisticians/data scientists in a real workforce setting. It also emphasizes the importance of good communication skills and other soft skills that are required by a biostatistician/data scientist to be effective in today’s work environment.

Practicum Sites

Participant practicum sites include:

  • Baycrest Hospital
  • Cancer Care Manitoba
  • Cancer Care Ontario
  • Centre for Addiction and Mental Health
  • Department of Family and Community Medicine, U of T
  • Dessa
  • Hospital for Sick Children
  • Institute for Clinical Evaluative Sciences
  • Institute for Work and Health
  • Princess Margaret Cancer Centre
  • Public Health Ontario
  • Roche Canada
  • Samuel Lunenfeld Research Institute
  • St. Michael’s Hospital
  • The Toronto General Hospital