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Resources: Statistical Modelling
Chance governs many aspects of our lives and predicting the probability of events is crucial to formulate and solve practical problems. Decisions about medicine, health, travel, engineering, investment, agriculture, telecommunications and safety are all made with consideration of the probability that favourable or unfavourable outcomes may occur. Such information is crucial for government, industry and individuals to manage risk.
Statistical Modelling is concerned with developing statistical and stochastic models for random phenomena, as well as analytical and computational tools for analysing those models.
At UQ Statistical Modelling is one of the Research Strengths of the Faculty of Engineering, Physical Sciences and Architecture (EPSA) currently being applied to classification problems, medical and pharmaceutical research, telecommunications and network performance, environmental modelling and warranty policy.
Researchers from these diverse fields work together with the support of the Mathematics Department, School of Physical Sciences and the Centres for Statistics (CSTAT) and Applied Dynamical Systems, Mathematical Analysis and Probability (CADSMAP). Such collaboration has allowed the University of Queensland to make a substantial contribution to classification methodology, medical statistics and to stochastic modelling in Engineering, Technology and Management.
The research strengths in Statistical Modelling include: classification problems, cluster and discriminant analyses, data mining, experimental design, generalised linear models, image analysis, machine learning, Markov Chain theory, mixture models, pattern recognition, simulation and stochastic modelling in biology, chemical kinetics, reliability and telecommunications.
As much of the research involved in statistical modelling requires access to advanced computational facilities it is also supported by UQ's Advanced Computational Modelling Centre (ACMC).
In addition to collaborations with overseas and other Australian universities, Statistical Modelling is strongly supported by the Australian Research Council with research from the group published in top international journals relevant to the field. Graduates in Statistiacl Modelling enjoy diverse career opportunities in economics, finance, marketing, education, engineering, manufacturing, health sciences and biotechnology.
Contact Details
Professor Geoff McLachlan
Statistical Modelling
Faculty of Engineering, Physical Sciences and Architecture
The University of Queensland
Brisbane QLD 4072 AUSTRALIA
Phone +61 7 3365 3277 Fax +61 7 3365 1477 admin@maths.uq.edu.au Web www.maths.uq.edu.au