In an experiment, data are collected to answer a research question. Often, resources are limited, and designing the experiment optimally/efficiently for achieving this aim can save experimental effort and thus reduce the cost while enabling researchers to draw reliable conclusions from the data. Optimal design of experiments is an area of Statistics where we rephrase the research question in statistical terms to find the (statistically motivated) optimality criterion that best reflects the aim of the experiment.
The area of optimal design of experiments complements the data analysis/inference side of Statistics. Before we can find an optimal/efficient design, we first need to establish the type of statistical analysis to be used on the experimental data to be collected. The methodology is not restricted to a specific application area, but can be used widely for experiments in, e.g., Chemistry, Engineering or Medicine.
Prof Stefanie Biedermann leads the research on design of experiments in the school. Some examples of her research topics are: