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Showing 25 course outlines from 4487 matches
3326
STATS 302
: Applied Multivariate Analysis2025 Semester One (1253)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
Restriction: STATS 767
3327
STATS 302
: Applied Multivariate Analysis2024 Semester One (1243)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
Restriction: STATS 767
3328
STATS 302
: Applied Multivariate Analysis2023 Semester One (1233)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
Restriction: STATS 767
3329
STATS 302
: Applied Multivariate Analysis2022 Semester One (1223)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
Restriction: STATS 767
3330
STATS 302
: Applied Multivariate Analysis2021 Semester One (1213)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
Restriction: STATS 767
3331
STATS 302
: Applied Multivariate Analysis2020 Semester One (1203)
Covers the exploratory analysis of multivariate data, with emphasis on the use of statistical software and reporting of results. Topics covered include: techniques for data display, dimension reduction and ordination, cluster analysis, multivariate ANOVA and associated methods.
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
Restriction: STATS 767
3332
STATS 310
: Introduction to Statistical Inference2025 Semester One (1253)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
3333
STATS 310
: Introduction to Statistical Inference2024 Semester One (1243)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
3334
STATS 310
: Introduction to Statistical Inference2023 Semester One (1233)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
3335
STATS 310
: Introduction to Statistical Inference2022 Semester One (1223)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
3336
STATS 310
: Introduction to Statistical Inference2021 Semester One (1213)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
3337
STATS 310
: Introduction to Statistical Inference2020 Semester One (1203)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
3338
STATS 313
: Advanced Topics in Probability2024 Semester Two (1245)
Characterisations of and relations between different kinds of random objects including random functions, random paths and random trees. Modes of convergence; the Law of Large Numbers and Central Limit Theorem.
Prerequisite: STATS 225
Restriction: STATS 710
Restriction: STATS 710
3339
STATS 313
: Advanced Topics in Probability2022 Semester Two (1225)
Characterisations of and relations between different kinds of random objects including random functions, random paths and random trees. Modes of convergence; the Law of Large Numbers and Central Limit Theorem.
Prerequisite: STATS 225
Restriction: STATS 710
Restriction: STATS 710
3340
STATS 320
: Applied Stochastic Modelling2025 Semester One (1253)
Construction, analysis and simulation of stochastic models, and optimisation problems associated with them. Poisson process, Markov chains, continuous-time Markov processes. Equilibrium distribution, reaching probabilities and times, transient behaviour. Use of R to simulate simple stochastic processes. Examples drawn from a range of applications including operations research, biology, and finance.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
3341
STATS 320
: Applied Stochastic Modelling2024 Semester One (1243)
Construction, analysis and simulation of stochastic models, and optimisation problems associated with them. Poisson process, Markov chains, continuous-time Markov processes. Equilibrium distribution, reaching probabilities and times, transient behaviour. Use of R to simulate simple stochastic processes. Examples drawn from a range of applications including operations research, biology, and finance.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
3342
STATS 320
: Applied Stochastic Modelling2023 Semester One (1233)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
3343
STATS 320
: Applied Stochastic Modelling2022 Semester One (1223)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
3344
STATS 320
: Applied Stochastic Modelling2021 Semester One (1213)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
3345
STATS 320
: Applied Stochastic Modelling2020 Semester One (1203)
Introduction to stochastic modelling, with an emphasis on queues and models used in finance. Behaviour of Poisson processes, queues and continuous time Markov chains will be investigated using theory and simulation.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
3346
STATS 325
: Stochastic Processes2025 Semester Two (1255)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Prerequisite: B+ or higher in STATS 125 or B or higher in ENGSCI 314 or STATS 210 or 225 or 320, and 15 points from ENGSCI 211, MATHS 208, 250
Restriction: STATS 721
Restriction: STATS 721
3347
STATS 325
: Stochastic Processes2024 Semester Two (1245)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Prerequisite: B+ or higher in STATS 125 or B or higher in ENGSCI 314 or STATS 210 or 225 or 320, and 15 points from ENGSCI 211, MATHS 208, 250
Restriction: STATS 721
Restriction: STATS 721
3348
STATS 325
: Stochastic Processes2023 Semester Two (1235)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Prerequisite: B+ or higher in STATS 125 or B or higher in ENGSCI 314 or STATS 210 or 225 or 320, and 15 points from ENGSCI 211, MATHS 208, 250
Restriction: STATS 721
Restriction: STATS 721
3349
STATS 325
: Stochastic Processes2022 Semester Two (1225)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Prerequisite: B+ or higher in STATS 125 or B or higher in STATS 210 or 225 or 320, and 15 points from ENGSCI 211, MATHS 208, 250
Restriction: STATS 721
Restriction: STATS 721
3350
STATS 325
: Stochastic Processes2021 Semester Two (1215)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Prerequisite: B+ or higher in STATS 125 or B or higher in STATS 210 or 225 or 320, and 15 points from ENGSCI 211, MATHS 208, 250
Restriction: STATS 721
Restriction: STATS 721
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