Research

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The Department of Statistics is one of the world's leading centres for research in Statistical Science.

Oxford University's Mathematical Sciences submission to the 2014 Research Excellence Framework, covering research from the Mathematical Institute and the Department of Statistics, was ranked overall best in the UK. The outcomes gave Oxford Mathematical Sciences the top ranking for research publications and for the impact of our research outside academia, and the equal top ranking for our research environment.

Research activity spans a wide range of modern and exciting developments in the subject. The main research groups in the Department are

 

As well as fundamental research in statistics and applied probability, there is much collaborative interdisciplinary research. Examples include:

Protein Informatics Group

The research interests of the Oxford Protein Informatics Group (OPIG) include protein structure prediction and protein interaction networks, combining both theoretical work and empirical analyses.

Statistical Genetics

The largest and most successful study of the genetics of common human diseases, the Wellcome Trust Case Control Consortium, was led from the Department by Professor Peter Donnelly with most of the methods development and analysis also in the Department. The Consortium's work, and subsequent collaborations, have been responsible for over 50 novel disease associations. The Department also has a major role in the 1,000 Genomes Project with Professor Gil McVean co-chairing the analysis group, in addition to the development of novel statistical methods and software that is now widely used in genetics.

R project

The R project is an international collaborative project that aims to provide a world-class environment for statistical computing, the development of new statistical methods and the graphical presentation of data. Professor Brian Ripley's group is one of the largest contributors to the project. Although originally developed for statistical research, R is now one of the most widely used of all statistical systems by researchers in many disciplines, and is close to universally used for teaching statistics at graduate level (and widely used for UGs). For just two examples, R has powered on-the-night election forecasting in the UK and in Austria, and much of the analysis of data from 'gene arrays' is done using R. It is also widely used in commercial settings, for instance in the pharmaceutical and financial industries, and for imaging.

Further information

Research Groups

Research blog