Experimental Design
Experimental design encompasses a wide array of methods for strategically collecting data. Effective data collection is critical for enabling decision making. While design of experiments (DOE) has origins in traditional response surface methodology, recent developments include modern computer simulation experiments of complex processes, in which DOE encompasses topics like active learning and Bayesian optimization.
Among the most important contributions of the field of statistics to science can be found in the area of Design of Experiments (DOE). The randomization emphasized in well-designed experiments is the gold standard for inferring causal effects of factors on a response. Drug discovery, quality control in manufacturing, and agricultural field trials all benefit from sound DOE. Faculty with expertise in the field have developed methodology for optimal screening designs and tests for non-additivity in block designs.