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microscope being used for statistical analysis

Our statisticians are world-leading experts. Statistical analysis undertaken by our Mathematicians are refining complex data sets and statistics to provide solutions for real-world challenges.

Bayesian statistical analysis

The UK government’s response to climate change risks draws heavily on the uncertainty analysis for future climate outcomes carried out by the Met Office in their UK Climate Projections 2009 (UKCP09) and 2018 (UKCP18).

The Met Office’s analyses used fundamental research carried out by our Statistics group into the Bayesian analysis of uncertainty for physical systems modelled by computer simulators.

This work, led by Professor Michael Goldstein, developed a very general probabilistic framework for linking mathematical models to the physical systems that they purport to represent. This framework takes account of all sources of uncertainty, including model and simulator imperfections.

Through UKCP18, our research is being used to help address the uncertainties in future climate and informing policy and investment decisions.

Statistical methods for modelling radiation exposure

Led by Professor Jochen Einbeck, our Statistics group have also produced cutting-edge models, methods and software for estimating levels of radiation doses in those exposed in a radiological incident. 

This has resulted in the development of statistical methodology that goes beyond traditional procedures, and these new methods are referenced in an ISO standard. They are also incorporated into the emergency response plans under RENEB, a European network specialising in radiation dose estimates.   

The team has developed an uncertainty quantification framework for the innovative gamma-H2AX protein biomarker. This enables quicker triage compared to other biomarkers, and hence greatly improved preparedness in case of a mass exposure scenario.

This has been adopted by Public Health England (PHE) into the standard operating procedures for its commercial biodosimetry (measurement of biological response as a surrogate for radiation dose) unit. Through collaboration with PHE and European partners a BioDose tools package has been produced to simplify and standardise uncertainty estimation in biodosimetry globally.

Find out more

Our Department of Mathematical Sciences combines world-leading research with a dedication to the learning experience of our students. Ranked 4th in the UK in The Complete University Guide 2023, we offer a unique blend of high-quality teaching and research across a wide range of disciplines and provide practical experience to support future careers and employment prospects.

Feeling inspired? Visit our Mathematical Sciences webpages to learn more about our postgraduate and undergraduate programmes.