# Search Course Outline

### Showing 25 course outlines from 3705 matches

2751

#### STATS 313

2022 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.
Subject: Statistics
Prerequisite: STATS 225
Restriction: STATS 710
2752

#### STATS 320

: Applied Stochastic Modelling
2024 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.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
2753

#### STATS 320

: Applied Stochastic Modelling
2023 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.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
2754

#### STATS 320

: Applied Stochastic Modelling
2022 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.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
2755

#### STATS 320

: Applied Stochastic Modelling
2021 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.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
2756

#### STATS 320

: Applied Stochastic Modelling
2020 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.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 207, 208, 220, BIOSCI 209
2757

#### STATS 325

: Stochastic Processes
2024 Semester Two (1245)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Subject: Statistics
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
2758

#### STATS 325

: Stochastic Processes
2023 Semester Two (1235)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Subject: Statistics
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
2759

#### STATS 325

: Stochastic Processes
2022 Semester Two (1225)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Subject: Statistics
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
2760

#### STATS 325

: Stochastic Processes
2021 Semester Two (1215)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Subject: Statistics
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
2761

#### STATS 325

: Stochastic Processes
2020 Semester Two (1205)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 320, with at least a B pass, 15 points from MATHS 208, 250, 253
Restriction: STATS 721
2762

#### STATS 326

: Applied Time Series Analysis
2024 Semester One (1243)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Subject: Statistics
Prerequisite: 15 points from ECON 211, ENGSCI 314, STATS 201, 208
Restriction: STATS 727
2763

#### STATS 326

: Applied Time Series Analysis
2023 Semester One (1233)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Subject: Statistics
Prerequisite: 15 points from ECON 211, ENGSCI 314, STATS 201, 208
Restriction: STATS 727
2764

#### STATS 326

: Applied Time Series Analysis
2022 Semester One (1223)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, ECON 211, STATS 201, 207, 208
Restriction: STATS 727
2765

#### STATS 326

: Applied Time Series Analysis
2021 Semester One (1213)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, ECON 211, STATS 201, 207, 208
Restriction: STATS 727
2766

#### STATS 326

: Applied Time Series Analysis
2021 Summer School (1210)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Subject: Statistics
Prerequisite: 15 points from BIOSCI 209, ECON 211, STATS 201, 207, 208
Restriction: STATS 727
2767

#### STATS 326

: Applied Time Series Analysis
2020 Semester One (1203)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 208, BIOSCI 209, ECON 221
Restriction: STATS 727
2768

#### STATS 326

: Applied Time Series Analysis
2020 Summer School (1200)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 208, BIOSCI 209, ECON 221
Restriction: STATS 727
2769

#### STATS 330

: Statistical Modelling
2024 Semester Two (1245)
Application of the generalised linear model and extensions to fit data arising from a range of sources including multiple regression models, logistic regression models, and log-linear models. The graphical exploration of data.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
2770

#### STATS 330

: Statistical Modelling
2024 Semester One (1243)
Application of the generalised linear model and extensions to fit data arising from a range of sources including multiple regression models, logistic regression models, and log-linear models. The graphical exploration of data.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
2771

#### STATS 330

: Statistical Modelling
2024 Summer School (1240)
Application of the generalised linear model and extensions to fit data arising from a range of sources including multiple regression models, logistic regression models, and log-linear models. The graphical exploration of data.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
2772

#### STATS 330

: Statistical Modelling
2023 Semester Two (1235)
Application of the generalised linear model and extensions to fit data arising from a range of sources including multiple regression models, logistic regression models, and log-linear models. The graphical exploration of data.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
2773

#### STATS 330

: Statistical Modelling
2023 Semester One (1233)
Application of the generalised linear model and extensions to fit data arising from a range of sources including multiple regression models, logistic regression models, and log-linear models. The graphical exploration of data.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
2774

#### STATS 330

: Statistical Modelling
2023 Summer School (1230)
Application of the generalised linear model and extensions to fit data arising from a range of sources including multiple regression models, logistic regression models, and log-linear models. The graphical exploration of data.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
2775

#### STATS 330

: Statistical Modelling
2022 Semester Two (1225)
Application of the generalised linear model and extensions to fit data arising from a range of sources including multiple regression models, logistic regression models, and log-linear models. The graphical exploration of data.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209