Note: This is the 2012–2013 edition of the eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or click here to jump to the newest eCalendar.
Program Requirements
Training in statistical theory and methods, applied data analysis, scientific collaboration, communication, and report writing by coursework and thesis.
Thesis Courses (24 credits)
-
BIOS 690 M.Sc. Thesis (24 credits)
Overview
Biostatistics : A review, appraisal of the performance, or application of, selected biostatistical methods, carried out under supervision.
Terms: Fall 2012, Winter 2013, Summer 2013
Instructors: There are no professors associated with this course for the 2012-2013 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)
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 2012
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)
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 2013
Instructors: Saarela, Olli (Winter)
-
MATH 523 Generalized Linear Models (4 credits)
Overview
Mathematics & Statistics (Sci) : Modern discrete data analysis. Exponential families, orthogonality, link functions. Inference and model selection using analysis of deviance. Shrinkage (Bayesian, frequentist viewpoints). Smoothing. Residuals. Quasi-likelihood. Sliced inverse regression. Contingency tables: logistic regression, log-linear models. Censored data. Applications to current problems in medicine, biological and physical sciences. GLIM, S, software.
Terms: Winter 2013
Instructors: Stephens, David (Winter)
-
MATH 533 Honours Regression and Analysis of Variance (4 credits)
Overview
Mathematics & Statistics (Sci) : This course consists of the lectures of MATH 423 but will be assessed at the 500 level.
Terms: Fall 2012
Instructors: Khalili Mahmoudabadi, Abbas (Fall)
-
MATH 556 Mathematical Statistics 1 (4 credits)
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 2012
Instructors: Neslehova, Johanna (Fall)
Fall
Prerequisite: MATH 357 or equivalent
-
MATH 557 Mathematical Statistics 2 (4 credits)
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 2013
Instructors: Asgharian-Dastenaei, Masoud (Winter)
Winter
Prerequisite: MATH 556
Faculty of Medicine—2012-2013 (last updated Dec. 20, 2012) (disclaimer)