Course summary

Our society revolves around variation, uncertainty and risk. By gaining a greater understanding of these variables through the study of statistics, we’re able to create systems and techniques that benefit areas as diverse as science, law and finance. Our Statistics research group explores a wide range of statistical theory and practice, often applying its findings in collaboration with researchers in related fields, such as informatics, geosciences, medicine and biomathematics. The group leads the interdisciplinary Centre for Statistics that spans across the whole breadth of the university, providing opportunities for collaborations with researchers in many different applied fields. The School of Mathematics is a vibrant community with researchers in many different, but related, fields - including Data Science. Our research is balanced between classical and Bayesian statistics. Particular areas of interest include, but not limited to, high-dimensional data, computationally intensive techniques, wavelets, nonparametric regression, extreme value theory, sampling and hidden process models. While the group has a strong theoretical base, a key component in the research relates to the interdisciplinary aspects of statistics with specific application areas including for example, ecology, geosciences, medicine, forensic science, law, and functional genomics data, such as gene expression microarrays.