Workshop on Optimizing Experimental Designs: Theory, Practice, and Applications

Abstract

The accurate and efficient measurement of observations is at the core of empirical scientific research. To ensure measurement is optimal, and thereby maximize inference, there has been a recent surge of interest among researchers in the design of experiments that lead to rapid accumulation of information about the phenomenon under study with the fewest possible measurements. Statisticians have contributed to this area by introducing methods of optimizing experimental design (OED). The methodology involves adapting the experimental design in real time as the experiment progresses. The purpose of this full-day workshop is to introduce the principles underlying OED, illustrate how to apply OED in practice using widely and freely available software tools (e.g., R) to showcase applications of OED in areas such as cognitive psychology, education and assessment, and machine learning, and provide a platform to share work on OED.


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