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Chapter 8

Chapter 8. Subjective Probability. Chapter 8, Subjective Probability. Learning Objectives: Uncertainty and public policy Subjective probability-assessment technique Heuristics and Biases Experts and Probability Assessment. Chapter 8,Subjective Probability.

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Chapter 8

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  1. Chapter 8 • Subjective Probability

  2. Chapter 8, Subjective Probability • Learning Objectives: • Uncertainty and public policy • Subjective probability-assessment technique • Heuristics and Biases • Experts and Probability Assessment

  3. Chapter 8,Subjective Probability • Subjective assessments of uncertainty are an important element of decision analysis. • In modern decision analysis subjective judgments of uncertainty can be made in terms of probability. • Need to develop a approach to measure the uncertainty that we feel

  4. Uncertainty and Public Policy • Fruit Frost, Farmers occasionally must decide whether to protect a crop from potentially damaging frost. • Decision must be made in terms of probability • Earthquake Prediction, Geologists are beginning to develop ways to assess the probability of major earthquakes.

  5. Uncertainty and Public Policy • Environment Impact Statements • Require assessments of the risks assessments of the risks associated with proposed projects. • Projects involving pesticides and herbicides, the chances of cancer and other health risks are assessed.

  6. Uncertainty and Public Policy • Public Policy and Scientific Research • Scientists learn of the possible presence of conditions that may require action by the government. • Medical Diagnosis • Many physicians in hospital intensive-care units (ICUs) have access to a complex computer system known as APACHE III.

  7. Uncertainty and Public Policy • APACHE III (Acute Physiology, Age, and Chronic Health Evaluation). • APACHE III evaluates the patient’s risk as a probability of dying either in the ICU or later in the hospital.

  8. Assessing Discrete Probabilities • There are three basic methods for assessing discrete probabilities • The first is to have decision maker assess the probability directly • “ What is your belief regarding the probability that event such and such will occur?

  9. Assessing Discrete Probabilities • The second method is to ask about the bets that the decision maker would be willing to place • The third approach adopts a thought-experiment strategy • Decision maker compares two lotterylike games, each of which can result in a prize.

  10. Assessing Discrete Probabilities • Third method approach • We would ask the decision maker to compare the lottery : Win prize A if the Lakers win Win prize B if the Lakers lose With the lottery Win prize A with known probability p. Win prize B with probability 1-p.

  11. Assessing Continuous Probabilities • Apply the technique of assess individual probabilities and then use these to plot a rough CDF. • The easiest way to use a continuous distribution in a decision tree or influence diagram is to approximate it with a discrete distribution.

  12. Pitfalls: Heuristics and Biases • Heuristics can be thought of as rules of thumb for accomplishing tasks. • They are easy and intuitive ways to deal with uncertain situations • It takes considerable practice before one is comfortable making probability assessments.

  13. Heuristics and Biases • Representatives: judge the probability that someone or something belongs to a particular category. • Availability: judge the probability that an event will occur according to the ease with similar events from memory. • Traffic accident and fire

  14. Heuristics and Biases • Motivational Bias: Incentives often exist that lead people to report probabilities that do not entirely reflect their true beliefs. • Awareness of the heuristics and biases may help individuals make better probability assessments.

  15. Experts and Probability Assessment • In complex problems, expert risk assessment plays a major role in the decision-making process. • The procedures for acquiring expert probability assessment has been established. • Every assessment protocol should include the following steps: • Background

  16. Experts and Probability • Background: The first important step • Identification and recruitment of experts • Motivating Experts • Structuring and Decomposition, this step identifies specific variables for which judgments are needed. • Probability-Assessment training

  17. Experts and Probability • Probability Elicitation and Verification, in this step the experts make the required probability assessment. • As part of this process, an expert may provide detailed chains of reasoning for the assessments. • Aggregation of Expert’s Probability Distribution

  18. Subjective probability • Constructing Distribution using RISKview • Step 1 through 8

  19. Chapter 8, Subjective Probability • Summary • Build model using subjective probability-assessment • Continuous and discrete probability assessing • Pitfalls and Heuristics • Expert probability assessment

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