Engineering statistics - Stephen B. Vardeman (Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, 2003)
In this entry we seek to put into perspective some of the ways in which statistical methods contribute to modern engineering practice. Engineers design and oversee the production, operation, and maintenance of the products and systems that under-gird modern technological society. Their work is built on the foundation of physical (and increasingly biological) science. However, it is of necessity often highly empirical, because there simply isn't scientific theory complete and simple enough to effectively describe all of the myriad circumstances that arise even in engineering design, let alone those encountered in production, operation, and maintenance. As a consequence, engineering is an inherently statistical enterprise. Engineers must routinely collect, summarize, and draw inferences based on data, and it is hard to think of a statistical method that has no potential use in modern engineering. The above said, it is possible to identify classes of statistical methods that have traditionally been associated with engineering applications and some that are increasingly important to the field. This encyclopedia entry will identify some of those and indicate their place in modern engineering practice, with no attempt to provide technical details of their implementation.
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