Master of Science in Mathematics & Statistics

Study qualitative and quantitative behaviour of differential equations, including flows, bifurcations, and manifolds, with applications in biological, physical, and social systems.

Explore how mathematical models are developed, analyzed and validated to represent real-world phenomena, using approaches such as differential equations, agent-based models, network models and stochastic processes.

Explore advanced, rotating topics in applied mathematics under faculty guidance through lectures, seminars, or project-based work.

Implement core computational methods in statistics such as Monte Carlo, MCMC, non-parametric techniques, and the EM algorithm.

Analyze time-to-event data using survival and hazard functions, censored data methods, and both parametric and semi-parametric models.

Explore advanced statistical modelling techniques for analyzing complex, longitudinal and clustered data, with a focus on both theory and practical implementation using statistical software.

An honours degree with the equivalent of a major or minor in mathematics or statistics, with a minimum B (73 per cent) average over the last two years of full-time equivalent study.

Complete application submission instructions may also be found on the Office of Graduate Studies webpage or in the Graduate Calendar.

Strong applicants with more diverse backgrounds will also be considered but are encouraged to contact the Graduate Program Coordinator or a potential advisor before applying.

Note that the department's undergraduate diploma in applied statistics fulfils the requirement of a minor equivalent in statistics.

For the statistics stream, it is required that students take the undergraduate course STAT*4340 Statistical Inference, if this course or its equivalent has not previously been taken.

Entry point for the M.Sc. in Math and Stats is Fall (September). The application deadline is July 31 (domestic) and February 28 (international). International applicants are encouraged to apply at least nine months in advance of their start date, and all applicants are advised to apply as early as possible due to supervisor availability.

The M.Sc. in Mathematics and Statistics is typically completed in two years of full-time study or four years of part-time study.

The Office of Graduate and Postdoctoral studies provides estimated annual full-time tuition, fees, and living expenses for graduate students at the University of Guelph: Tuition, Fees and Cost of Living.

Full funding is typically provided for full-time, thesis-based students (who do not receive external funding) through a combination of scholarships, teaching assistantships, and/or research assistantships. For more information about funding your graduate studies at Guelph, please visit Funding Graduate Studies.

Students pursuing the Mathematical area of emphasis must complete at least two core courses from different groups:

1. Group A
   • MATH*6020 Scientific Computing
2. Group B
   • MATH*6010 Analysis
   • MATH*6031 Functional Analysis
3. Group C
   • MATH*6051 Mathematical Modelling
   • MATH*6071 Biomathematics

See the Graduate Calendar for complete course requirements.

Students pursuing the Statistical area of emphasis must complete at least two of the following core courses:

• STAT*6801 Statistical Learning
• STAT*6802 Generalized Linear Models and Extensions
• STAT*6841 Computational Statistical Inference

Learn more about collaborative specializations and eligibility in the Graduate Calendar.

M.Sc. students may enhance their studies by pursuing a collaborative specialization alongside their degree:

• Artificial Intelligence: Available to thesis students conducting research with an artificial intelligence focus. Learn more about CSAI.
• One Health: Available to students completing thesis or major research project work with a One Health focus. Learn more about One Health.

Learn more about collaborative specializations and eligibility in the Graduate Calendar.

The Department of Mathematics and Statistics is an active department with 23 faculty and over 50 graduate students. Specific research areas include:

• Biomathematics, Differential Equations and Scientific Computing
• Computational and Bayesian Statistics
• Epidemiology, Biostatistics, and Bioinformatics
• Machine Learning and Artificial Intelligence
• Mathematical and Statistical Pedagogy
• Network Modelling and Spatial-Temporal Statistics
• Operations Research
• Statistical Finance and Probability
• Quantum Information and Matrix Analysis

Learn more about collaborative specializations and eligibility in the Graduate Calendar.