Professor Sue Lewis , Professor Phil Prescott , Dr Stefanie Biedermann, Dr Dave Woods and Professor Wei LuiActivities include researching new methodologies in several areas of the design and analysis of experiments such as factorial experiments and optimal design.
Projects are available in a variety of areas, including
Further details about the group can be found on the Design webpage..
The design and analysis of experiments is vital to ensure efficient use of resources in all areas of business, industry, science and medicine which use experimentation. New experimental methods and equipment constantly motivate new statistical problems, in the planning of experiments and in analysing the resulting data.
Projects are available in developing core methodology, which will be applicable to many different areas of experimentation, and in developing sound statistical solutions to specific experimental problems. Methodological projects include developing methods for designing experiments for generalized linear mixed models and nonlinear models, as well as issues related to randomization-based justifications for methods of analysis.
Many experiments in medicine and biology lead to data with discrete responses or lifetimes and new design problems often arise. In the pharmaceutical industry there is increasing interest in pharmacokinetics and the models which arise in their study. The design of experiments for these experiments is only just starting to be addressed.
A variety of projects is also underway to improve methods of experimentation and engineering design in industry. The projects range from research into experiments where certain factors cannot be fully controlled through to collaborative work with engineering departments and industry on improving their products and processes. In factorial experimentation current work is the development of methods of economic experimentation when a large number of factors are to be investigated, through screening groups of factors.