The Second Course in Statistics: Design and Analysis of Experiments?

Statistics departments are facing rapid growth in enrollments and increases in demand for courses. This article discusses the use of design and analysis of experiments (DAE) as a nonterminal second course in statistics for undergraduate statistics majors, minors, and other students seeking exposure to the practice of statistics beyond the introductory course. DAE is a gateway to approaching statistical thinking as data-based problem solving by exposing students to statistical, computational, data, and communication skills in the second course. Given the somewhat antiquated view of design and deemphasis of classical design of experiments topics in the new ASA curriculum guidelines, DAE may seem an odd choice for the second course; however, it exposes students to the breadth of the statistical problem-solving process, explores foundational issues of the discipline, and is accessible to students who have not yet finished their advanced mathematical training. These skills remain essential in the data science era as students must be equipped to understand the potential and peril of found data using the principles of design. While DAE may not be the appropriate second course for all statistics programs, it provides a strong foundation for causal inference and experimental design for students pursuing a B.S. in Statistics in a program housed in a department of statistics.[Received December 2014. Revised July 2015.]