Fall 2023
Classes begin: August 30
Fall Reading Break: October 6, 10 and 11
Makeup Days:ÌýThursday, Nov. 30 is the make-up lecture day for Monday classes and will follow a Monday scheduleÌý(seeÌýwww.mcgill.ca/importantdates/key-dates)
Classes end: December 5
BIOS 601
Epi: Intro&Statistical Models
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Epidemiology and Biostatistics
- Prerequisites: Permission of instructor. Undergraduate course in mathematical statistics at level of MATH 324.
BIOS 612
Adv. Generalized Linear Models
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: Statistical methods for multinomial outcomes, overdispersion, and continuous and categorical correlated data; approaches to inference (estimating equations, likelihood-based methods, semi-parametric methods); analysis of longitudinal data; theoretical content and applications.
Offered by: Epidemiology and Biostatistics
- Terms
- Instructors
- Shirin Golchi, Luke Hagar
BIOS 624
Data Analysis & Report Writing
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: Common data-analytic problems. Practical approaches to complex data. Graphical and tabular presentation of results. Writing reports for scientific journals, research collaborators, consulting clients.
Offered by: Epidemiology and Biostatistics
- Prerequisites: MATH 533 Analysis of Variance and Regression. MATH 523 Generalized Linear Models.
BIOS 694
Special Topics in Biostats 4
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: Special topics in biostatistics.
Offered by: Epidemiology and Biostatistics
- Prerequisite: Permission of the instructor.
Topic:
Machine Learning
This course aims to interconnect the traditional concepts of biostatistics with the emerging methodologies of machine learning. The objective is to foster a deeper understanding of the insights emerging from machine learning and enrich the analytical skills developed from conventional graduate-level Biostatistics courses. The course will introduce students to innovative machine learning algorithms and data analytics techniques that are critical for prediction, classification, and data pattern recognition tasks as well as their challenges and issues. Primarily, we'll focus on the application of these techniques within the realms of biostatistics and epidemiology. By the end of this course, students will be better equipped to navigate health science problems with an enriched statistical toolkit.
BIOS 702
Ph.D. Proposal
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: Essential skills for thesis writing and defence, including essential elements of research proposals, methodological development and application, and presentation.
Offered by: Epidemiology and Biostatistics
- Note: Required for Ph.D. students
- Terms
- This course is not scheduled for the 2024 academic year
- Instructors
- There are no professors associated with this course for the 2024 academic year
MATH 533
Regression and ANOVA
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
MATH 556
Mathematical Statistics 1
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
Winter 2024
Classes begin: January 4
Winter Reading Break: March 4 to 8
Makeup Days:ÌýThursday, April 11 is the make-up lecture day for Monday classes and will follow a Monday schedule. (seeÌýwww.mcgill.ca/importantdates/key-dates)
Classes end: April 12
BIOS 602
Epidemiology:Regression Models
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Epidemiology and Biostatistics
- Prerequisites: Permission of instructor. MATH 556 and BIOS 601, or their equivalents.
BIOS 702
Ph.D. Proposal
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: Essential skills for thesis writing and defence, including essential elements of research proposals, methodological development and application, and presentation.
Offered by: Epidemiology and Biostatistics
- Note: Required for Ph.D. students
- Terms
- This course is not scheduled for the 2024 academic year
- Instructors
- There are no professors associated with this course for the 2024 academic year
MATH 523
Generalized Linear Models
4 Credits
Offered in the:
- Fall
- Winter
- Summer
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.
Offered by: Mathematics and Statistics
MATH 557
Mathematical Statistics 2
4 Credits
Offered in the:
- Fall
- Winter
- Summer
Mathematics & Statistics (Sci): Sufficiency, minimal and complete sufficiency, ancillarity. Fisher and Kullback-Leibler
information. Elements of decision theory. Theory of estimation and hypothesis testing from the Bayesian and frequentist perspective. Elements of asymptotic statistics including large-sample behaviour of maximum likelihood estimators, likelihood-ratio tests, and chi-squared goodness-of-fit tests.
Offered by: Mathematics and Statistics