Statistical Engineering: An Idea Whose Time Has Come?

TL;DR

Statistical engineering is proposed as a new discipline to address complex, unstructured problems that traditional methods struggle with, emphasizing the development of a theoretical foundation for its practice.

Contribution

The paper advocates for formalizing the theory of statistical engineering to complement its practical applications and advance the discipline.

Findings

Highlights the need for a new paradigm in statistics for complex problems.

Documents the current state of the theoretical development of statistical engineering.

Encourages further research to establish a solid theoretical foundation.

Abstract

Several authors, including the American Statistician (ASA), have noted the challenges facing statisticians when attacking large, complex, unstructured problems, as opposed to well-defined textbook problems. Clearly, the standard paradigm of selecting the one "correct" statistical method for such problems is not sufficient; a new paradigm is needed. Statistical engineering has been proposed as a discipline that can provide a viable paradigm to attack such problems, used in conjunction with sound statistical science. Of course, in order to develop as a true discipline, statistical engineering needs a well-developed theory, not just a formal definition and successful case studies. This article documents and disseminates the current state of the underlying theory of statistical engineering. Our purpose is to provide a vehicle for applied statisticians to further enhance the practice of statistics, and for academics so interested to continue development of the underlying theory of statistical engineering.