Document Type

Conference Paper

Publication Date


Publication Title

Proceedings of the American Society for Engineering Management 2015 International Annual Conference



Conference Name

American Society for Engineering Management International Annual Conference, 7-10 October 2015, Indianapolis, Indiana, USA


In the ASEM-IAC 2012, Cotter (2012) summarized prior works that led to the proposal for statistical engineering, identified the gaps in knowledge that statistical engineering needs to address, explored additional gaps in knowledge not addressed in the prior works, set forth a working definition of and body of knowledge for statistical engineering, and set forth proposals of potential systems contributions the Engineering Management profession could make toward the development of statistical engineering. In 2014, the ASQ Statistics Division, DOT&E, NASA, and IDA co-sponsored a Statistical Engineering Agreement to jointly research development of the discipline of statistical engineering. The statistics community has continued to frame statistical engineering within the context of the general linear model (GLM). However, incorporating deterministic engineering causal models within the GLM framework leaves missing links of conditional dependencies, yields models that are difficult to fit or that may not converge to a unique solution, and may not increase the understanding of physical causal processes in dynamic stochastic systems. Integration of engineering specific deterministic causal models within stochastic models to provide additional knowledge of the risk of variance from expected response is a key gap in knowledge that must be addressed to realize Statistical Engineering as a discipline. This paper updates research into integrating deterministic engineering models as system dynamic causal components of functional causal Bayesian networks within a state-space framework to model joint deterministic-stochastic dynamic causal effects.


Included with the kind permission of the publisher.

Copyright, American Society for Engineering Management, 2015.

Original Publication Citation

Cotter, T. S. (2015). Statistical engineering: A causal-stochastic modeling research update. In S. Long, E-H. Ng, & A. Squire (Eds.), Proceedings of the American Society for Engineering Management 2015 International Annual Conference (pp. 1-6). American Society for Engineering Management (ASEM).