Applied Statistics Research
As well as developing novel methodology, Applied Statistics researchers engage in interdisciplinary research, encouraging the cross-fertilisation of ideas and the synthesis of statistical and biological knowledge. This work extends beyond the School to other groups in the University including Food Biosciences, Pharmacy, Agriculture and the Walker Institute. Areas of current research cover the following broad topics:
Population, Evolutionary and Statistical Genetics
Novel technologies in genetics have created new challenges for the analysis of available data. Many projects within this rapidly moving field make use of Bayesian methodology and stochastic simulation. Broad areas of application include medicine, conservation and forensics, and research topics include finding disease gene locations and analysing DNA profile evidence.
Medical Statistics, Epidemiology and Biostatistical Modelling
Staff working in this area have interests covering all aspects of experimental and observational study conduct. This ranges from the design of suitable trials prior to the collection of any data, through to model fitting and model checking after a study has been completed. Particular areas of current research include methodology for sequential trials, techniques for meta-analysis, capture-recapture methods, mixture modelling and dose-finding studies.
Ecological Modelling and Statistical Climatology
Research within this area includes: mathematical and statistical modelling of complex ecological systems, be they natural or managed; statistical modelling of climatic data; and statistical methods for understanding the relationship between climate and ecological systems. The use of Bayesian methods to address these issues, and the implications for study design and data collection are of particular interest.
Further information about the research interests of individual staff members can be found in the table below.
| Staff | Research interests | |
| Dr Karen Ayres |  |
Statistical genetics, population genetics, forensic statistics, relatedness testing, epidemiology |
| Dr Fazil Baksh | Statistical genetics, genetic epidemiology, pharmacogenetics, genomewide association studies | |
| Professor Dankmar Böhning |  |
Biostatistical modelling, capture-recapture modelling, likelihood-based inference, mixture models, review research, meta-analysis |
| Dr Mike Dennett |  |
Statistical climatology, intercrops, statistical crop growth models |
| Dr Andrew Meade | Evolution, computational biology, phylogeny, Markov chain Monte Carlo | |
| Dr Sue Todd |  |
Medical statistics, clinical trials, adaptive designs, epidemiology |
| Dr Fiona Underwood |  |
Designing sampling & monitoring strategies, Bayesian methods, interdisciplinary applications in conservation, climate, agriculture |
| Dr Yinghui (Echo) Zhou |  |
Medical statistics, clinical trials, Bayesian methods |