Subjects offered

A number of subjects are available in the Statistics stream, with progressively more being made available in the more senior years. This is reflective of the need for a sound understanding of mathematics principles first before moving towards statistics.

ASEARC is still being developed and more subjects will be made available as the collaboration develops.

Undergraduate subjects

Linear & Generalised Linear Models

Through shared notes updated across the collaboration, each university delivers the subject to their own students. This subject looks at how to investigate relationships between variables arising from observational studeis and designed experiments. Subject covers model fitting, exponential family of distributions, maximum likelihood estimation, linear regression, amongst other topics.

Statistical Inference

Through shared notes updated across the collaboration, each university delivers the subject to their own students . This subject looks at how to make inferences about unknown quantities from observed data. Subject covers estimation methods, maximum likelihood and minimum variance unbiased estimation, hypothesis testing, evaluating tests, bootstrap method, amongst other topics.

Sample Surveys and Experimental Design

Delivered by the University of Wollongong, this subject will develop skills in designing and analysing statistical investigations. Statistical computing is an essential part of the course. Topics covered include:

• Experimental designs (completely randomised, randomised complete block, Latin Square, factorial);
• the analysis of the data arising from these designs; steps in conducting a sample survey;
• methods such as simple random sampling and stratified sampling, number raised and ratio estimation.

Further information please click here.

Applied Bayesian Methods

Delivered by the University of Newcastle (STAT3120). this subject will introduce students to Bayesian thinking and methods from an applied point of view; covering the use of prior information, Bayes rule and inference in standard situations such as proportions, means and relationships between variables. An applied view on Markov chain Monte Carlo methods will also be given. These methods are becoming popular among applied statisticians and analysts from disciplines such as, Economics, Quantitative finance, Health, Environmental science, Engineering and other applied areas, especially because prior information can be incorporated directly into analyses in a sensible way.

Further information please click here.

Total Quality Management, at both year 3 and postgraduate levels.

STAT374 will be delivered by the University of Newcastle (STAT3100). The subject will introduce students to Total Quality Management. TQM is a scientific approach for management and employees to be involved in the continuous improvement of processes underlying the production of goods and services. This approach is fundamental in business, industry, evidence-based medicine and many other disciplines.

Further information please click here.

Postgraduate subjects

Sample Surveys and Experimental Design

Same content as above subject but includes additional work and content at postgraduate level.

Applied Bayesian Methods

Same content as above subject but includes additional work and content at postgraduate level.

Total Quality Management

Same content as above subject but includes additional work and content at postgraduate level.

Statistical Consulting

Delivered from the University of Wollongong, a student who successfully completes this subject should be able to:

• conduct efficiently a consulting session with a client;
• find information on statistical methodology using the resources of the Library and the World Wide Web ;
• explain the important principles behind designing and conducting an experiment or sample survey;
• determine appropriate statistical procedures to use on a wide variety of data sets;
• apply and interpret procedures from a statistical package.

Further information please click here.

Advanced Data Analysis

Delivered from the University of Wollongong, after successful completion of this subject, students should be able to;

• understand the concept of goodness of fit, and be able to describe some tests of fit and apply them
• be able to derive smooth tests of fit for certain specified distributions, and similar distributions
• understand how to construct certain nonparametric tests by first presenting the data in a contingency table
• be able to non-parametrically analyse certain types of data.

Further information please click here.

Subjects offered

A number of subjects are available in the Statistics stream, with progressively more being made available in the more senior years. This is reflective of the need for a sound understanding of mathematics principles first before moving towards statistics.

ASEARC is still being developed and more subjects will be made available as the collaboration develops.

Undergraduate subjects

Linear & Generalised Linear Models

Through shared notes updated across the collaboration, each university delivers the subject to their own students. This subject looks at how to investigate relationships between variables arising from observational studeis and designed experiments. Subject covers model fitting, exponential family of distributions, maximum likelihood estimation, linear regression, amongst other topics.

Statistical Inference

Through shared notes updated across the collaboration, each university delivers the subject to their own students . This subject looks at how to make inferences about unknown quantities from observed data. Subject covers estimation methods, maximum likelihood and minimum variance unbiased estimation, hypothesis testing, evaluating tests, bootstrap method, amongst other topics.

Sample Surveys and Experimental Design

Delivered by the University of Wollongong, this subject will develop skills in designing and analysing statistical investigations. Statistical computing is an essential part of the course. Topics covered include:

• Experimental designs (completely randomised, randomised complete block, Latin Square, factorial);
• the analysis of the data arising from these designs; steps in conducting a sample survey;
• methods such as simple random sampling and stratified sampling, number raised and ratio estimation.

Further information please click here.

Applied Bayesian Methods

Delivered by the University of Newcastle (STAT3120). this subject will introduce students to Bayesian thinking and methods from an applied point of view; covering the use of prior information, Bayes rule and inference in standard situations such as proportions, means and relationships between variables. An applied view on Markov chain Monte Carlo methods will also be given. These methods are becoming popular among applied statisticians and analysts from disciplines such as, Economics, Quantitative finance, Health, Environmental science, Engineering and other applied areas, especially because prior information can be incorporated directly into analyses in a sensible way.

Further information please click here.

Total Quality Management, at both year 3 and postgraduate levels.

STAT374 will be delivered by the University of Newcastle (STAT3100). The subject will introduce students to Total Quality Management. TQM is a scientific approach for management and employees to be involved in the continuous improvement of processes underlying the production of goods and services. This approach is fundamental in business, industry, evidence-based medicine and many other disciplines.

Further information please click here.

Postgraduate subjects

Sample Surveys and Experimental Design

Same content as above subject but includes additional work and content at postgraduate level.

Applied Bayesian Methods

Same content as above subject but includes additional work and content at postgraduate level.

Total Quality Management

Same content as above subject but includes additional work and content at postgraduate level.

Statistical Consulting

Delivered from the University of Wollongong, a student who successfully completes this subject should be able to:

• conduct efficiently a consulting session with a client;
• find information on statistical methodology using the resources of the Library and the World Wide Web ;
• explain the important principles behind designing and conducting an experiment or sample survey;
• determine appropriate statistical procedures to use on a wide variety of data sets;
• apply and interpret procedures from a statistical package.

Further information please click here.

Advanced Data Analysis

Delivered from the University of Wollongong, after successful completion of this subject, students should be able to;

• understand the concept of goodness of fit, and be able to describe some tests of fit and apply them
• be able to derive smooth tests of fit for certain specified distributions, and similar distributions
• understand how to construct certain nonparametric tests by first presenting the data in a contingency table
• be able to non-parametrically analyse certain types of data.

Further information please click here.