What Every Engineer Should Know About Decision Making Under Uncertainty
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A01=John X. Wang
Author_John X. Wang
Category=GPQ
Category=KJMD
control
decision tree methods
distribution
engineering
engineering decision analysis models
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
optimization strategies
probability
process
project management uncertainty
random
regression modeling
risk assessment techniques
simulation
spreadsheet analysis
statistical
table
variable
Product details
- ISBN 9780824708085
- Weight: 589g
- Dimensions: 152 x 229mm
- Publication Date: 01 Jul 2002
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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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.
Wang, John X.
