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Program Requirements

Training in statistical theory and methods, applied data analysis, scientific collaboration, communication, and report writing by coursework and thesis.

Thesis Courses (21 credits)

• BIOS 690 M.Sc. Thesis (21 credits)

  Offered by: Epidemiology and Biostatistics (Faculty of Medicine and Health Sciences)

  Administered by: Graduate Studies

  Overview

  Biostatistics : A review, appraisal of the performance, or application of, selected biostatistical methods, carried out under supervision.

  Terms: Fall 2021, Winter 2022

  Instructors: There are no professors associated with this course for the 2021-2022 academic year.

Required Courses (24 credits)

Students exempted from any of the courses listed below must replace them with complementary course credits, at the 500 level or higher, chosen in consultation with the student's academic adviser or supervisor.

• BIOS 601 Epidemiology: Introduction and Statistical Models (4 credits)

  Offered by: Epidemiology and Biostatistics (Faculty of Medicine and Health Sciences)

  Administered by: Graduate Studies

  Overview

  Biostatistics : Examples of applications of statistics and probability in epidemiologic research. Source of epidemiologic data (surveys, experimental and non-experimental studies). Elementary data analysis for single and comparative epidemiologic parameters.

  Terms: Fall 2021

  Instructors: Hanley, James Anthony (Fall)

  • Prerequisites: Permission of instructor. Undergraduate course in mathematical statistics at level of MATH 324.

• BIOS 602 Epidemiology: Regression Models (4 credits)

  Offered by: Epidemiology and Biostatistics (Faculty of Medicine and Health Sciences)

  Administered by: Graduate Studies

  Overview

  Biostatistics : Multivariable regression models for proportions, rates and their differences/ratios; Conditional logic regression; Proportional hazards and other parametric/semi-parametric models; unmatched, nested, and self-matched case-control studies; links to Cox's method; Rate ratio estimation when "time-dependent" membership in contrasted categories.

  Terms: Winter 2022

  Instructors: Coulombe, Janie (Winter)

  • Prerequisites: Permission of instructor. MATH 556 and BIOS 601, or their equivalents.

• MATH 523 Generalized Linear Models (4 credits)

  Offered by: Mathematics and Statistics (Faculty of Science)

  Overview

  Mathematics & Statistics (Sci) : Exponential families, link functions. Inference and parameter estimation for generalized linear models; model selection using analysis of deviance. Residuals. Contingency table analysis, logistic regression, multinomial regression, Poisson regression, log-linear models. Multinomial models. Overdispersion and Quasilikelihood. Applications to experimental and observational data.

  Terms: Winter 2022

  Instructors: Neslehova, Johanna (Winter)

  • Winter

  • Prerequisite: MATH 423 or MATH 533 or EPIB 697.

• MATH 533 Regression and Analysis of Variance (4 credits)

  Offered by: Mathematics and Statistics (Faculty of Science)

  Overview

  Mathematics & Statistics (Sci) : Multivariate normal and chi-squared distributions; quadratic forms. Multiple linear regression estimators and their properties. General linear hypothesis tests. Prediction and confidence intervals. Asymptotic properties of least squares estimators. Weighted least squares. Variable selection and regularization. Selected advanced topics in regression. Applications to experimental and observational data.

  Terms: Fall 2021

  Instructors: Khalili Mahmoudabadi, Abbas (Fall)

  • Prerequisites: MATH 357, MATH 247 or MATH 251.

• MATH 556 Mathematical Statistics 1 (4 credits)

  Offered by: Mathematics and Statistics (Faculty of Science)

  Overview

  Mathematics & Statistics (Sci) : Distribution theory, stochastic models and multivariate transformations. Families of distributions including location-scale families, exponential families, convolution families, exponential dispersion models and hierarchical models. Concentration inequalities. Characteristic functions. Convergence in probability, almost surely, in Lp and in distribution. Laws of large numbers and Central Limit Theorem. Stochastic simulation.

  Terms: Fall 2021

  Instructors: Khalili Mahmoudabadi, Abbas (Fall)

  • Fall

  • Prerequisite: MATH 357 or equivalent

• MATH 557 Mathematical Statistics 2 (4 credits)

  Offered by: Mathematics and Statistics (Faculty of Science)

  Overview

  Mathematics & Statistics (Sci) : Sampling theory (including large-sample theory). Likelihood functions and information matrices. Hypothesis testing, estimation theory. Regression and correlation theory.

  Terms: Winter 2022

  Instructors: Genest, Christian (Winter)

  • Winter

  • Prerequisite: MATH 556