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What Every Engineer Should Know About Decision Making Under Uncertainty [Paperback]

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  • Category: Books (Business & Economics)
  • Author:  Wang, John X.
  • Author:  Wang, John X.
  • ISBN-10:  0367447002
  • ISBN-10:  0367447002
  • ISBN-13:  9780367447007
  • ISBN-13:  9780367447007
  • Publisher:  CRC Press
  • Publisher:  CRC Press
  • Pages:  328
  • Pages:  328
  • Binding:  Paperback
  • Binding:  Paperback
  • SKU:  0367447002-11-MPOD
  • SKU:  0367447002-11-MPOD
  • Item ID: 105103631
  • Seller: ShopSpell
  • Ships in: 2 business days
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  • Delivery by: Oct 13 to Oct 15
  • Notes: Brand New Item. Not shipped to AK, HI, APO, FPO, AE.

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.

1. Engineering: Making Hard Decisions under Uncertainty 2. Engineering Judgment for Discrete Uncertain Variables 3. Decision Analysis Involving Continuous Uncertain Variables 4. Correlation of Random Variables and Estimating Confidence 5. Performing Engineering Predictions 6. Engineering Decision Variables  Analysis and Optimization 7. Project Scheduling and Budgeting under Uncertainty 8. Process Control  Decisions based on Charts and Indexes 9. Engineering Decision Making: A New ParadigmThis book introduces general techniques for thinking systematically and quantitatively about uncertainty in engineering decision problems. It shows how conditional expectations and conditional cumulative distributions can be estimated in a simulation model.USCopyright ? 2002 by Marcel Dekker, Inc.
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