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Showing 25 course outlines from 4473 matches

3301

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
3302

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
3303

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
3304

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
3305

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
3306

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
3307

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
3308

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
3309

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
3310

STATS 302

: Applied Multivariate Analysis
2025 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.
Subject: Statistics
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
3311

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
3312

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
3313

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
3314

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
3315

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
3316

STATS 310

: Introduction to Statistical Inference
2025 Semester One (1253)
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
3317

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
3318

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
3319

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
3320

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
3321

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
3322

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
3323

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
3324

STATS 320

: Applied Stochastic Modelling
2025 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.
Subject: Statistics
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
3325

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