Statistics is an essential part of science, providing the mathematical language and techniques necessary for understanding and dealing with chance and uncertainty in nature. It involves the design, collection, analysis and interpretation of numerical data, with the aim of extracting patterns and other useful information.

Examples include:

  • analysis of DNA and protein sequences
  • construction of evolutionary trees from genetic data
  • improvement of medical treatments via experimental designs
  • assessment of drought conditions through meteorological data.

A main feature of statistics is the development and use of statistical and probabilistic models for random phenomena, which can be analysed and used to make principled predictions and decisions.

Examples of such models can be found in:

  • biology (genetics, population modelling)
  • finance (stock market fluctuations, insurance claims)
  • physics (quantum mechanics/computing)
  • medicine (epidemiology, spread of HIV/AIDS)
  • telecommunications (internet traffic, mobile phone calls)
  • reliability (safety of oil rigs, aircraft failure).

Statistics and Probability Group

We are recognised internationally for our active and dynamic research programs across several areas of statistics.

Our diverse research strengths include:

  • bioinformatics
  • biostatistics
  • computational statistics
  • discriminant and cluster analyses
  • experimental design
  • image analysis
  • machine learning
  • mixture modelling
  • Monte Carlo simulation
  • multivariate analysis
  • applied probability and stochastic processes.

We have established ongoing collaborations with other disciplines, particularly in the biological and medical sciences, bioinformatics, engineering and information technology, as well as with industry and government bodies.  

Available projects

See our statistics and probability projects.

People

Academic

Adjunct and honorary