# Search Course Outline

### Showing 25 course outlines from 3703 matches

2826

#### 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

2827

#### 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

2828

#### 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

2829

#### 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

2830

#### STATS 710

: Probability Theory2020 Semester Two (1205)

Prerequisite: STATS 310, 320 or 325

2831

#### 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

2832

#### 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

2833

#### 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

2834

#### 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

2835

#### STATS 720

: Stochastic Processes2020 Semester One (1203)

Prerequisite: STATS 320 or 325

2836

#### 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

2837

#### 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

2838

#### 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

2839

#### STATS 721

: Foundations of Stochastic Processes2021 Semester Two (1215)

Restriction: STATS 325

2840

#### STATS 721

: Foundations of Stochastic Processes2020 Semester Two (1205)

Restriction: STATS 325

2841

#### 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

2842

#### 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

2843

#### 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

2844

#### 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

2845

#### 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

2846

#### 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

2847

#### 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

2848

#### STATS 726

: Time Series2021 Semester Two (1215)

Prerequisite: STATS 210, and 320 or 325

2849

#### STATS 726

: Time Series2020 Semester Two (1205)

No pre-requisites or restrictions

2850

#### STATS 727

: Foundations of Applied Time Series Analysis2021 Semester One (1213)

Fundamentals of applied time series analysis. Topics include: components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas are presented.

Prerequisite: 15 points from BIOSCI 209, ECON 221, STATS 201, 207, 208, 707

Restriction: STATS 326

Restriction: STATS 326

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