M.Sc. Non-Thesis
Training in statistical theory and methods, applied data analysis, scientific collaboration, communication, and report writing by coursework and project.
The M.Sc. non-thesis program is designed to expose students to a wide range of topics including statistical methods for epidemiology, generalized linear models, survival analysis, longitudinal data, and clinical trials. Skills in data analysis, statistical consulting, communication, and report writing are emphasized, and students graduate ready to work in the pharmaceutical and biotechnology industries, in government, or in academic medical research.
Research Project (6 credits)
BIOS 630
Res Project/Practic in Biostat
6 Credits
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: Critical appraisal of the biostatistical literature related to a specific statistical methodology. Topic to be approved by faculty member who will direct student and evaluate the paper.
Offered by: Epidemiology and Biostatistics
- Restriction: Limited to non-thesis M.Sc. students who have completed requirements.
- Terms
- Instructors
- There are no professors associated with this course for the 2024 academic year
Review the
project guidelines.
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
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 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.
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 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
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
Complementary Courses (18 credits)
18 credits of coursework, at the 500 level or higher, chosen in consultation with the student's academic adviser or supervisor.
Program Director and Advisor:
alexandra.schmidt [at] mcgill.ca (Alexandra Schmidt)
M.Sc. Thesis
Training in statistical theory and methods, applied data analysis, scientific collaboration, communication, and report writing by coursework and thesis.
M.Sc. thesis students study a foundational set of courses, and write a thesis on a topic of their choice. Thesis students should have a strong interest in research. These students are well-placed to either continue in a Ph.D. program or to work in academic research in statistics; they will also have relevant qualifications for the pharmaceutical industry and government.
Thesis Course (21Ìýcredits)
BIOS 690
M.Sc. Thesis
21 Credits
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: A review, appraisal of the performance, or application of, selected biostatistical methods, carried out under supervision.
Offered by: Epidemiology and Biostatistics
- Terms
- Instructors
- There are no professors associated with this course for the 2024 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
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 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.
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 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
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
Program Director and Advisor:
alexandra.schmidt [at] mcgill.ca (Alexandra Schmidt)
Ph.D.
Students will study theoretical and applied statistics and related fields; the program will train them to become independent scientists able to develop and apply statistical methods in medicine and biology and make original contributions to the theoretical and scientific foundations of statistics in these disciplines. Graduates will be prepared to develop new statistical methods as needed and apply new and existing methods in a range of collaborative projects. Graduates will be able to communicate methods and results to collaborators and other audiences, and teach biostatistics to biostatistics students, students in related fields, and professionals in academic and other settings.
Thesis
A thesis for the doctoral degree must constitute original scholarship and must be a distinct contribution to knowledge. It must show familiarity with previous work in the field and must demonstrate the ability to plan and carry out research, organize results, and defend the approach and conclusions in a scholarly manner. The research presented must meet current standards of the discipline; as well, the thesis must clearly demonstrate how the research advances knowledge in the field. Finally, the thesis must be written in compliance with norms for academic and scholarly expression and for publication in the public domain.
Required Courses
BIOS 701
Ph.D. Comprehensive Exam
Offered in the:
- Fall
- Winter
- Summer
Biostatistics: Assessment of student's ability to assimilate and apply statistical theory and methods for biostatistics.
Offered by: Epidemiology and Biostatistics
- Restriction (s): Enrolment in the Ph.D. in Biostatistics
- Terms
- Instructors
- There are no professors associated with this course for the 2024 academic year
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
For additional information see:
BIOS700 Comp Exam.pdfÌý
BIOS701 Comp Exam.pdf
BIOS702Protocol.pdf
Complementary Courses (46 credits)
0-28 credits from the following list: (if a student has not already successfully completed them or their equivalent).
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 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 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.
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 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
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
12 credits (chosen and approved in consultation with the student's academic adviser), at the 500 level or higher, in statistics/biostatistics.
6 credits (chosen and approved in consultation with the student's academic adviser), at the 500 level or higher, in related fields (e.g., epidemiology, social sciences, biomedical sciences).
Program Director and Advisor:
alexandra.schmidt [at] mcgill.ca (Alexandra Schmidt)