Probability & Statistics is the interdisciplinary study of theoretical probability, applied probaility, mathematical statistics, and applied statistics.

Research in Probability and Statistics at McMaster is highly interdisciplinary, and reaches beyond the department into the Faculties of Science, Medical, Engineering and Business. Research interests include: Theoretical Probability (large deviations, stochastic differential equations, martingales) Applied Probability (stochastic genetics, queueing systems) and Mathematical Statistics (inferential methods, model-validity, outliers, multivariate analysis) and Applied Statistics (environmental hazards, animal abundance, genetics, climatology, pharmaceutics, and mortality).

Order statistics, distribution theory

Epidemiology, ecology, applied statistics, Mixed models, environmental science

Computational statistics

Statistical inference, order statistics, outliers

Stochastic processes, interacting particle systems

Stochastic models, genetics and medicine, probability bounds

Classification, clustering, computational statistics, data science, machine learning, mixture models

Data science, evolutionary algorithms, high-dimensional problems, machine learning, mixture models

Statistical inference, reliability, discrete modeling