The aim of STA1006S is to provide students who intend to major in Mathematical Statistics with a solid foundation in the mathematical aspects of statistics required in the training of a professional statistician. The material for STA1006S places more emphasis on the theoretical and mathematical aspects of Statistics than STA1000S. As a result, the course will be taught at a much faster pace than STA1000S. The breadth and depth of the STA1006S syllabus means that the course demands from the students a hard working attitude and an effective study strategy.
Mathematical Statistics Stream
Please see the Science Faculty Handbook for more information on course requirements

STA1006S – Statistics for Mathematical Disciplines

STA2004F – Statistical Theory and Inference

STA2005S – Linear Models

STA3041F – Markov Processes and Time Series

STA3043S – Decision Theory and Generalized Linear Models

STA3045F – Advanced Stochastic Processes
The course covers the analysis and modelling of stochastic processes. Topics include Poisson processes, random walks, measure theoretic probability, martingales, stopping theorems, Brownian motion, stochastic integration and Ito calculus, copula and taildependency, extreme value theory, and continuoustime Markov chains.
Applied Statistics Stream
Please see the Commerce Faculty Handbook for more information on course requirements

STA1000F/S – Statistics 1000

STA1001F – Statistics 1001

STA1007S – Bionumeracy

STA1100S – Statistics 1000 (Commerce Education Development Unit)

STA1101F/H – Statistics 1001 (Commerce Education Development Unit)

STA2007F – Applied Statistical Modelling

STA2020F – Business Statistics

STA2030S – Theory of Statistics

STA3022F – Research and Survey Statistics

STA3030F – Inferential Statistics

STA3036S – Operational Research Techniques