Even the best engineering undergraduates often have little enthusiasm for our statistics courses. Some of their disinterest is really traceable not just to a skepticism about whether using our apparently boring methods will help them be better engineers, but to an even more fundamental ignorance of what engineers do and what kinds of environments they work in. Where a statistician has the luxury of giving a second course in engineering statistics (like a statistical quality control (SQC) course), some part of that course can be aimed at providing not just statistical methodology, but also a proper context for that methodology. This paper discusses ideas in this direction, some of which I have used in an SQC course for industrial engineering students and are documented at http://www.public.iastate.edu/~vardeman/IE361/ie361vard.html,a course Web page, and others of which I am still thinking about how to utilize.
The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education