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Showing 25 course outlines from 4482 matches
3426
STATS 709
: Predictive Modelling2024 Semester Two (1245)
Predictive modelling forecasts likely future outcomes based on historical and current data. Following an advanced introduction to statistics and data analysis, the course will discuss concepts for modern predictive modelling and machine learning.
Prerequisite: COMPSCI 130, MATHS 108, and 15 points from STATS 101, 108, or equivalent
Restriction: STATS 201, 207, 208, 210, 225, 707, 765
Restriction: STATS 201, 207, 208, 210, 225, 707, 765
3427
STATS 710
: Probability Theory2025 Semester Two (1255)
Fundamental ideas in probability theory; sigma-fields, laws of large numbers, characteristic functions, the Central Limit Theorem, modes of convergence. Advanced topics may include Poisson random measures, random trees, Lévy processes, random spatial models. Students will undertake assigned individual research projects based on a journal article or advanced textbook, including a detailed explanation of the techniques of probability theory exemplified therein.
Prerequisite: B+ or higher in STATS 225 or 15 points from STATS 310, 320, 325
3428
STATS 710
: Probability Theory2024 Semester Two (1245)
Fundamental ideas in probability theory; sigma-fields, laws of large numbers, characteristic functions, the Central Limit Theorem.
Prerequisite: B+ or higher in STATS 225 or 15 points from STATS 310, 320, 325
3429
STATS 710
: Probability Theory2022 Semester Two (1225)
Fundamental ideas in probability theory; sigma-fields, laws of large numbers, characteristic functions, the Central Limit Theorem.
Prerequisite: B+ or higher in STATS 225 or 15 points from STATS 310, 320, 325
3430
STATS 710
: Probability Theory2021 Semester Two (1215)
Fundamental ideas in probability theory; sigma-fields, laws of large numbers, characteristic functions, the Central Limit Theorem.
Prerequisite: B+ or higher in STATS 225 or 15 points from STATS 310, 320, 325
3431
STATS 710
: Probability Theory2020 Semester Two (1205)
Fundamental ideas in probability theory; sigma-fields, laws of large numbers, characteristic functions, the Central Limit Theorem.
Prerequisite: STATS 310, 320 or 325
3432
STATS 720
: Stochastic Processes2024 Semester One (1243)
Stochastic models and their applications. Discrete and continuous-time jump Markov processes. A selection of topics from point processes, renewal theory, Markov decision processes, stochastic networks, inference for stochastic processes, simulation of stochastic processes, and computational methods using R.
Prerequisite: STATS 320 or 325
3433
STATS 720
: Stochastic Processes2023 Semester One (1233)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Prerequisite: STATS 320 or 325
3434
STATS 720
: Stochastic Processes2022 Semester One (1223)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Prerequisite: STATS 320 or 325
3435
STATS 720
: Stochastic Processes2021 Semester One (1213)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Prerequisite: STATS 320 or 325
3436
STATS 720
: Stochastic Processes2020 Semester One (1203)
Continuous-time jump Markov processes. A selection of topics from: point processes, renewal theory, martingales, Brownian motion, Gaussian processes and inference for stochastic processes.
Prerequisite: STATS 320 or 325
3437
STATS 721
: Foundations of Stochastic Processes2025 Semester Two (1255)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Prerequisite: 15 points from STATS 125, 210, 225, 320 with at least a B+ and 15 points from MATHS 208, 250, 253
Restriction: STATS 325
Restriction: STATS 325
3438
STATS 721
: Foundations of Stochastic Processes2024 Semester Two (1245)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Prerequisite: 15 points from STATS 125, 210, 225, 320 with at least a B+ and 15 points from MATHS 208, 250, 253
Restriction: STATS 325
Restriction: STATS 325
3439
STATS 721
: Foundations of Stochastic Processes2023 Semester Two (1235)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Restriction: STATS 325
3440
STATS 721
: Foundations of Stochastic Processes2022 Semester Two (1225)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Restriction: STATS 325
3441
STATS 721
: Foundations of Stochastic Processes2021 Semester Two (1215)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Restriction: STATS 325
3442
STATS 721
: Foundations of Stochastic Processes2020 Semester Two (1205)
Fundamentals of stochastic processes. Topics include: generating functions, branching processes, Markov chains, and random walks.
Restriction: STATS 325
3443
STATS 722
: Foundations of Financial Mathematics2020 Semester Two (1205)
Fundamentals of financial mathematics. Topics include: mean-variance portfolio theory; options, arbitrage and put-call relationships; introduction of binomial and Black-Scholes option pricing models; compound interest, annuities, capital redemption policies, valuation of securities, sinking funds; varying rates of interest, taxation; duration and immunisation; introduction to life annuities and life insurance mathematics.
Prerequisite: 15 points at Stage II in Statistics or BIOSCI 209, and 15 points at Stage II in Mathematics
Restriction: STATS 370
Restriction: STATS 370
3444
STATS 723
: Stochastic Methods in Finance2022 Semester One (1223)
Contingent claims theory in discrete and continuous time. Risk-neutral option pricing, Cox-Ross-Rubinstein and Black-Scholes models, stochastic calculus, hedging and risk management.
Prerequisite: STATS 125 and 370, or 15 points from STATS 210, 225, 325
3445
STATS 723
: Stochastic Methods in Finance2021 Semester One (1213)
Contingent claims theory in discrete and continuous time. Risk-neutral option pricing, Cox-Ross-Rubinstein and Black-Scholes models, stochastic calculus, hedging and risk management.
Prerequisite: STATS 125 and 370, or 15 points from STATS 210, 225, 325
3446
STATS 723
: Stochastic Methods in Finance2020 Semester One (1203)
Contingent claims theory in discrete and continuous time. Risk-neutral option pricing, Cox-Ross-Rubinstein and Black-Scholes models, stochastic calculus, hedging and risk management.
Prerequisite: STATS 125 and 370, or 15 points from STATS 210, 225, 325
3447
STATS 726
: Time Series2025 Semester Two (1255)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Prerequisite: STATS 210, and 15 points from STATS 326, 786
3448
STATS 726
: Time Series2024 Semester Two (1245)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Prerequisite: STATS 210, and 15 points from STATS 326, 786
3449
STATS 726
: Time Series2023 Semester Two (1235)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Prerequisite: STATS 210, and 320 or 325
3450
STATS 726
: Time Series2022 Semester Two (1225)
Stationary processes, modelling and estimation in the time domain, forecasting and spectral analysis.
Prerequisite: STATS 210, and 320 or 325
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