Applied Bayesian Methods 
and
Total Quality Management

Background

Subjects STAT373 (Special Topics in Probability and Statistics 3) and STAT374 (Special Topics in Applied Statistics 3) are reserved to cover topics selected for a particular year.  For 2010, STAT373 will cover ‘Applied Bayesian Methods’, and STAT374 will cover ‘Total Quality Management’.  These topics were chosen to provide a more complete grounding for students studying statistics. 

These subjects are available to year three students in addition to the normal core units, and year four students as electives.  Honours students may also select these subjects as electives.  Please liaise with your course coordinator for further information.

What are they?

STAT373 covering Applied Bayesian Methods

The course introduces 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.

This is identified as STAT3120 in the University of Newcastle syllabus.

Assumed knowledge for enrolling to this subject is completion of the UoN STAT2010 subject or completion of the second year inference course, as well as an appreciation of regression and ANOVA models from a Bayesian perspective.

View the full course content here.

STAT374 covering Total Quality Management

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.

This is identified as STAT6100 in the University of Newcastle syllabus.

Assumed knowledge is nil.

View the full course content here.

Why take the subjects?

The content of these subjects are aimed at those students wishing to gain a broader understanding of statistics in addition to the normal syllabus.  The subjects are strongly recommended for students considering a career as a Statistician or working closely with statistics.

How will the subjects be run?

The course will be run in the spring session (semester 2) from Newcastle as part of the ASEARC* project.  STAT373 (Applied Bayesian Methods) will be delivered through the Access Grid Room** (AGR), and STAT374 (Total Quality Management) will be conducted through distance education.  Regardless of either of these two methods, you will also be able to interact with lecturers and other students via the eLearning system.

Further details will be provided closer to Semester 2.

* The ASEARC project is a collaboration between a number of universities to better coordinate course resources including course delivery.  Subjects may be provided by a university with the particular expertise and delivered to other universities through various means including interactive media and distance learning.

** The AGR technology has been described as video-conferencing on steroids.  The lecturer in one location (say Wollongong) will have a class of local students as well as a "virtual" classroom in another location (say Newcastle).  While students in Wollongong have the usual visual and audio interaction with the lecturer, students in Newcastle will be able to view the lecturer on a big screen, hear what is being said, and instantly view notations on a whiteboard in their room as the notations are written on a whiteboard in Wollongong.  Likewise, the lecturer and students in Wollongong will be able to hear and see the students in Newcastle and receive any notes made on whiteboard in Newcastle.  This may seem a little strange at first but the technology aims to simulate the usual classroom experience and students in previous classes seemed to adapt very quickly.  Further details about this teaching arrangement will be covered during the first class.