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Chapter12 Value of Information

Chapter12 Value of Information. Making Hard Decisions. Weiguo Yang Nov 2001. Value of information: Basics. Probability and Perfect information Perfect information: always correct Expected value of information EV = 0: the information won’t change your decision

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Chapter12 Value of Information

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  1. Chapter12 Value of Information Making Hard Decisions Weiguo Yang Nov 2001

  2. Value of information: Basics • Probability and Perfect information • Perfect information: always correct • Expected value of information • EV = 0: the information won’t change your decision • EV is maximum the information is perfect

  3. Expected value of perfect information • EVPI • Difference between EPV of without and with that information • Computation • Expand decision trees to include decisions with perfect information

  4. Expected value of imperfect information • EVII • Difference between EPV of without and with that information • Computation • Expand decision trees to include decisions with imperfect information • Reverse the order of node • Calculate EVII using conditional probability

  5. Value of perfect information in complex problems • Continuous probability distribution • Change “sum” into “integrate” • Construct discrete approximation • Many uncertainty events • Solving the complex influence diagram or decision tree

  6. Discussions • Value of information, sensitivity analysis and structuring • VI in sensitivity analysis: the more VI, the more need to study the uncertainty • Value of information and nonmonetary objectives • Quantify objective ( eg. time required) • Value of information and experts • Calculating EVPI and EVII with Precision Tree

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