What Every Engineer Should Know About Decision Making Under Uncertainty

By: John X. Wang

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Paperback | 2 December 2019 | Edition Number 1

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322 Pages

Dimensions(cm)
22.9 x 15.2 x 1.7

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Covering the prediction of outcomes for engineering decisions through regression analysis, this succinct and practical reference presents statistical reasoning and interpretational techniques to aid in the decision making process when faced with engineering problems. The author emphasizes the use of spreadsheet simulations and decision trees as important tools in the practical application of decision making analyses and models to improve real-world engineering operations. He offers insight into the realities of high-stakes engineering decision making in the investigative and corporate sectors by optimizing engineering decision variables to maximize payoff.

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