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Showing 25 course outlines from 747 matches
551
STATS 108
: Statistics for Commerce2023 Semester One (1233)
The standard Stage I Statistics course for the Faculty of Business and Economics or for Arts students taking Economics courses. Its syllabus is as for STATS 101, but it places more emphasis on examples from commerce.
Restriction: STATS 101, 102, 107, 191
552
STATS 108
: Statistics for Commerce2023 Summer School (1230)
The standard Stage I Statistics course for the Faculty of Business and Economics or for Arts students taking Economics courses. Its syllabus is as for STATS 101, but it places more emphasis on examples from commerce.
Restriction: STATS 101, 102, 107, 191
553
STATS 125
: Probability and its Applications2023 Semester Two (1235)
Probability, conditional probability, Bayes theorem, random walks, Markov chains, probability models. Illustrations will be drawn from a wide variety of applications including: finance and economics; biology; telecommunications, networks; games, gambling and risk.
Corequisite: ENGSCI 111 or MATHS 108 or 110 or 120 or 130
Restriction: STATS 210
Restriction: STATS 210
554
STATS 125
: Probability and its Applications2023 Semester One (1233)
Probability, conditional probability, Bayes theorem, random walks, Markov chains, probability models. Illustrations will be drawn from a wide variety of applications including: finance and economics; biology; telecommunications, networks; games, gambling and risk.
Corequisite: ENGSCI 111 or MATHS 108 or 110 or 120 or 130
Restriction: STATS 210
Restriction: STATS 210
555
STATS 150
: Lies, Damned Lies, and Statistics2023 Semester Two (1235)
Examines the uses, limitations and abuses of statistical information in a variety of activities such as polling, public health, sport, law, marketing and the environment. The statistical concepts and thinking underlying data-based arguments will be explored. Emphasises the interpretation and critical evaluation of statistically based reports as well as the construction of statistically sound arguments and reports. Some course material will be drawn from topics currently in the news.
No pre-requisites or restrictions
556
STATS 201
: Data Analysis2023 Semester Two (1235)
A practical course in the statistical analysis of data. Interpretation and communication of statistical findings. Includes exploratory data analysis, the analysis of linear models including two-way analysis of variance, experimental design and multiple regression, the analysis of contingency table data including logistic regression, the analysis of time series data, and model selection.
Prerequisite: 15 points from STATS 101-108, 191
Restriction: STATS 207, 208, BIOSCI 209
Restriction: STATS 207, 208, BIOSCI 209
557
STATS 201
: Data Analysis2023 Semester One (1233)
A practical course in the statistical analysis of data. Interpretation and communication of statistical findings. Includes exploratory data analysis, the analysis of linear models including two-way analysis of variance, experimental design and multiple regression, the analysis of contingency table data including logistic regression, the analysis of time series data, and model selection.
Prerequisite: 15 points from STATS 101-108, 191
Restriction: STATS 207, 208, BIOSCI 209
Restriction: STATS 207, 208, BIOSCI 209
558
STATS 201
: Data Analysis2023 Summer School (1230)
A practical course in the statistical analysis of data. Interpretation and communication of statistical findings. Includes exploratory data analysis, the analysis of linear models including two-way analysis of variance, experimental design and multiple regression, the analysis of contingency table data including logistic regression, the analysis of time series data, and model selection.
Prerequisite: 15 points from STATS 101-108, 191
Restriction: STATS 207, 208, BIOSCI 209
Restriction: STATS 207, 208, BIOSCI 209
559
STATS 208
: Data Analysis for Commerce2023 Semester Two (1235)
A practical course in the statistical analysis of data. There is a heavy emphasis in this course on the interpretation and communication of statistical findings. Topics such as exploratory data analysis, the analysis of linear models including two-way analysis of variance, experimental design and multiple regression, the analysis of contingency table data including logistic regression, the analysis of time series data, and model selection will be covered.
Prerequisite: 15 points from STATS 101-108, 191
Restriction: STATS 201, 207, BIOSCI 209
Restriction: STATS 201, 207, BIOSCI 209
560
STATS 208
: Data Analysis for Commerce2023 Semester One (1233)
A practical course in the statistical analysis of data. There is a heavy emphasis in this course on the interpretation and communication of statistical findings. Topics such as exploratory data analysis, the analysis of linear models including two-way analysis of variance, experimental design and multiple regression, the analysis of contingency table data including logistic regression, the analysis of time series data, and model selection will be covered.
Prerequisite: 15 points from STATS 101-108, 191
Restriction: STATS 201, 207, BIOSCI 209
Restriction: STATS 201, 207, BIOSCI 209
561
STATS 208
: Data Analysis for Commerce2023 Summer School (1230)
A practical course in the statistical analysis of data. There is a heavy emphasis in this course on the interpretation and communication of statistical findings. Topics such as exploratory data analysis, the analysis of linear models including two-way analysis of variance, experimental design and multiple regression, the analysis of contingency table data including logistic regression, the analysis of time series data, and model selection will be covered.
Prerequisite: 15 points from STATS 101-108, 191
Restriction: STATS 201, 207, BIOSCI 209
Restriction: STATS 201, 207, BIOSCI 209
562
STATS 210
: Statistical Theory2023 Semester Two (1235)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing.
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125
Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
563
STATS 210
: Statistical Theory2023 Semester One (1233)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing.
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125
Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
564
STATS 210
: Statistical Theory2023 Summer School (1230)
Probability, discrete and continuous distributions, likelihood and estimation, hypothesis testing.
Prerequisite: 15 points from ENGSCI 111, ENGGEN 150, STATS 125
Corequisite: 15 points from MATHS 208, 250, ENGSCI 211 or equivalent
565
STATS 220
: Data Technologies2023 Semester One (1233)
Explores the processes of data acquisition, data storage and data processing using current computer technologies. Students will gain experience with and understanding of the processes of data acquisition, storage, retrieval, manipulation, and management. Students will also gain experience with and understanding of the computer technologies that perform these processes.
Prerequisite: 15 points at Stage I in Computer Science or Statistics
566
STATS 225
: Probability: Theory and Applications2023 Semester One (1233)
Covers the fundamentals of probability through theory, methods, and applications. Topics should include the classical limit theorems of probability and statistics known as the laws of large numbers and central limit theorem, conditional expectation as a random variable, the use of generating function techniques, and key properties of some fundamental stochastic models such as random walks, branching processes and Poisson point processes.
Prerequisite: B+ or higher in ENGGEN 150 or ENGSCI 111 or STATS 125, or a B+ or higher in MATHS 120 and 130
Corequisite: 15 points from ENGSCI 211, MATHS 208, 250
567
STATS 240
: Design and Structured Data2023 Semester Two (1235)
An introduction to research study design and the analysis of structured data. Blocking, randomisation, and replication in designed experiments. Clusters, stratification, and weighting in samples. Other examples of structured data.
Prerequisite: STATS 101 or 108
Restriction: STATS 340
Restriction: STATS 340
568
STATS 255
: Optimisation and Data-driven Decision Making2023 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.
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
Restriction: ENGSCI 255
569
STATS 302
: Applied Multivariate Analysis2023 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.
Prerequisite: ENGSCI 314 or STATS 201 or 208
Restriction: STATS 767
Restriction: STATS 767
570
STATS 310
: Introduction to Statistical Inference2023 Semester One (1233)
Estimation, likelihood methods, hypothesis testing, multivariate distributions, linear models.
Prerequisite: STATS 210 or 225, and 15 points from MATHS 208, 250 or equivalent
Restriction: STATS 732
Restriction: STATS 732
571
STATS 320
: Applied Stochastic Modelling2023 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.
Prerequisite: 15 points from STATS 125, 210, 225 and 15 points from STATS 201, 208, 220, or ENGSCI 314
572
STATS 325
: Stochastic Processes2023 Semester Two (1235)
Introduction to stochastic processes, including generating functions, branching processes, Markov chains, random walks.
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
Restriction: STATS 721
573
STATS 326
: Applied Time Series Analysis2023 Semester One (1233)
Components, decompositions, smoothing and filtering, modelling and forecasting. Examples and techniques from a variety of application areas.
Prerequisite: 15 points from ECON 211, ENGSCI 314, STATS 201, 208
Restriction: STATS 727
Restriction: STATS 727
574
STATS 330
: Statistical Modelling2023 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.
Prerequisite: ENGSCI 314 or STATS 201 or 208
575
STATS 330
: Statistical Modelling2023 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.
Prerequisite: ENGSCI 314 or STATS 201 or 208