Controlled experiments, and the statistical analysis of data resulting from these experiments, form a bedrock of the scientific process. To address scientific questions of interest in a valid and efficient way, such experiments require an appropriate plan for how the data are to be collected and, related, how they are to be analyzed after collection. This statistical area of research is often known as Design of Experiments (DOE), but the name Design and Analysis of Experiments (DAE) is perhaps preferable because it explicitly emphasizes the importance of the analysis component in planning an experiment.
The study of design and analysis of experiments is as old as the field of statistics. With the need for statistical methods becoming prominent through agricultural studies, the development of valid methods for experiments was one of those needs, for example to compare different fertilizers or different crops. This is reflected by the seminal book “The Design of Experiments” by Sir Ronald A. Fisher, published in 1935. Many books and papers on aspects of design and analysis of experiments have seen the light of day since that time, and it remains a very active area of research. This is also true in the era of big data: the quantity of data cannot and should not substitute for careful collection of high quality data.
While initially with a smaller focus, reflected in a different name (“First Midwest Conference for New Directions in Experimental Design”), a series of conferences that became the DAE conference series was started at The Ohio State University in 2000. The focus almost immediately broadened from the Midwest of the United States of America to all of the United States and Canada. In terms of participants, the conference series has from the very beginning attracted researchers from all over the world.
Among the goals of the DAE conference series is the provision of support and encouragement to junior researchers in the field of design and analysis of experiments, and to stimulate interest in topics of practical relevance to science and industry. The emphasis on interactions between junior and senior researchers, through mentoring sessions and roundtables, help with accomplishing these goals.
A DAE Vision Statement can be found here.