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Showing 25 course outlines from 3702 matches

2726

STATS 255

: Optimisation and Data-driven Decision Making
2024 Semester One (1243)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 108 or 120 or 130 or 162 or 199 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
2727

STATS 255

: Optimisation and Data-driven Decision Making
2023 Semester One (1233)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 108 or 120 or 130 or 162 or 199 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
2728

STATS 255

: Optimisation and Data-driven Decision Making
2022 Semester One (1223)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 108 or 120 or 130 or 150 or 153 or 162 or 199 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
2729

STATS 255

: Optimisation and Data-driven Decision Making
2021 Semester One (1213)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 120 or 130 or 150 or 153 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
2730

STATS 255

: Optimisation and Data-driven Decision Making
2020 Semester Two (1205)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 120 or 130 or 150 or 153 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
2731

STATS 255

: Optimisation and Data-driven Decision Making
2020 Semester One (1203)
Explores methods for using data to assist in decision making in business and industrial applications. Software packages will be used to solve practical problems. Topics such as linear programming, transportation and assignment models, network algorithms, queues, Markov chains, inventory models, simulation, analytics and visualisation will be considered.
Subject: Statistics
Prerequisite: ENGSCI 211 or STATS 201 or 208, or a B+ or higher in either MATHS 120 or 130 or 150 or 153 or STATS 101 or 108, or a concurrent enrolment in either ENGSCI 211 or STATS 201 or 208
Restriction: ENGSCI 255
2732

STATS 301

: Statistical Programming and Modelling using SAS
2021 Semester Two (1215)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
2733

STATS 301

: Statistical Programming and Modelling using SAS
2021 Summer School (1210)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
2734

STATS 301

: Statistical Programming and Modelling using SAS
2020 Semester Two (1205)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
2735

STATS 301

: Statistical Programming and Modelling using SAS
2020 Summer School (1200)
Introduction to the SAS statistical software with emphasis on using SAS as a programming language for purposes of database manipulation, simulation, statistical modelling and other computer-intensive methods.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 785
2736

STATS 302

: Applied Multivariate Analysis
2024 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.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
2737

STATS 302

: Applied Multivariate Analysis
2023 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.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
2738

STATS 302

: Applied Multivariate Analysis
2022 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.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
2739

STATS 302

: Applied Multivariate Analysis
2021 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.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
2740

STATS 302

: Applied Multivariate Analysis
2020 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.
Subject: Statistics
Prerequisite: 15 points from STATS 201, 207, 208, BIOSCI 209
Restriction: STATS 767
2741

STATS 310

: Introduction to Statistical Inference
2024 Semester One (1243)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Subject: Statistics
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
2742

STATS 310

: Introduction to Statistical Inference
2023 Semester One (1233)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Subject: Statistics
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
2743

STATS 310

: Introduction to Statistical Inference
2022 Semester One (1223)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Subject: Statistics
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
2744

STATS 310

: Introduction to Statistical Inference
2021 Semester One (1213)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Subject: Statistics
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
2745

STATS 310

: Introduction to Statistical Inference
2020 Semester One (1203)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Subject: Statistics
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
2746

STATS 313

: Advanced Topics in Probability
2024 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.
Subject: Statistics
Prerequisite: STATS 225
Restriction: STATS 710
2747

STATS 313

: Advanced Topics in Probability
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
2748

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
2749

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
2750

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