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
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STA1006S – Statistics for Mathematical Disciplines
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STA2004F – Statistical Theory and Inference
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STA2005S – Linear Models
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STA3041F – Markov Processes and Time Series
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STA3043S – Decision Theory and Generalized Linear Models
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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 tail-dependency, extreme value theory, and continuous-time Markov chains.
Applied Statistics Stream
Please see the Commerce Faculty Handbook for more information on course requirements
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STA1000F/S – Statistics 1000
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STA1001F – Statistics 1001
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STA1007S – Bionumeracy
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STA1100S – Statistics 1000 (Commerce Education Development Unit)
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STA1101F/H – Statistics 1001 (Commerce Education Development Unit)
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STA2007F – Applied Statistical Modelling
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STA2020F – Business Statistics
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STA2030S – Theory of Statistics
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STA3022F – Research and Survey Statistics
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STA3030F – Inferential Statistics
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STA3036S – Operational Research Techniques