expand hardware now; Delay HW = delay hardware decision; OT = project finished on time; Late = project finished late; FP = favorable software progress in the first five months; NP = learning nothing new in the first five months; and UP = unfavorable software progress in the first five months. Consider the decision tree shown in Figure 1 where the nodes have been numbered for easy reference. The decision choices at the initial decision node (D1) are: SW Only, Delay HW, and HW Now.
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Quantitative Values Project: Homeowner Master Bathroom Remodel To incorporate quantitative values of expected value and probability into the risk management plan for my master bathroom remodel project will be a challenge. The homeowner is taking on the task of trying to do much of the remodel work himself. Hence the risk is related to human failure. Since the homeowner does not have extensive experience in some of the remodeling tasks, there is no history that can be used to calculate failure
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Decision Trees Using TreePlan 16 16.1 TREEPLAN OVERVIEW TreePlan is a decision tree add-in for Microsoft Excel 97–2007 for Windows and Macintosh. TreePlan helps you build a decision tree diagram in an Excel worksheet using dialog boxes. Decision trees are useful for analyzing sequential decision problems under uncertainty. Your decision tree model may include various controllable alternatives (e.g., whether to introduce a new product, whether to bid on a new project) and uncontrollable uncertainties
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Executive Summary Oceanview is considering a property bid of $5 million, which would require them to submit a deposit of 10% of the bid amount. Should the bid be rejected, the deposit will be refunded. However, should Oceanview win the bid, they must still consider the approval of zoning change to built the condominium. If the zoning is approved, the building can start. If not, the 10% deposit will be forfeited. From the flow summarized above, we can see that the green light to carry on building
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faithfully maintained file indicates the client's baseline condition and treatment goals. It is also a memorandum concerning whether these goals were accomplished (Hartsell, 2008). When faced with a request for records, I would employ a systematic decision-making approach verses a heuristic approach. The systematic approach I would use would both investigate the ethical issues and the resolve the dilemma. I would have a seven-step process. I would define carefully the issues and parties involved, scan
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1 PROBABILISTIC APPROACHES: SCENARIO ANALYSIS, DECISION TREES AND SIMULATIONS In the last chapter, we examined ways in which we can adjust the value of a risky asset for its risk. Notwithstanding their popularity, all of the approaches share a common theme. The riskiness of an asset is encapsulated in one number – a higher discount rate, lower cash flows or a discount to the value – and the computation almost always requires us to make assumptions (often unrealistic) about the nature of risk
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Chapter 9: Capacity Planning and Facility Location Overview This chapter defines capacity planning and location analysis and explains the steps and factors considered when making these types of decisions. The relationship between capacity planning and location analysis is described. The use of decision support tools for capacity planning and location analysis is described. Answers to Discussion Questions in Textbook 1. Explain why capacity planning is important to a business. Having
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Value of Information in Decision Trees 19 19.1 VALUE OF INFORMATION Useful concept for Evaluating potential information-gathering activities Comparing importance of multiple uncertainties 19.2 EXPECTED VALUE OF PERFECT INFORMATION Several computational methods Flipping tree, moving an event set of branches, appropriate for any decision tree Payoff table, most appropriate only for single-stage tree (one set of uncertain outcomes with no subsequent decisions) Expected improvement All three
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Exercice 1 1 / Decision Tree 2/ The recommended strategy * EV(init. prop) = $750’000 * EV*(c.offer) = 0.1*400’000 + 0.2* 750’000 + 0.12*1’500’000 + 0.5*600’000 = $670’000 the EV*(c.offer) is a better solution since its expected value is smaller than EV(init.prop). 3/ risk profile Amount | Probability | 0 $ | 0.08 | 400 $ | 0.1 | 600 $ | 0.5 | 750 $ | 0.2 | 1500 $ | 0.15 | Exercice 2 1 / Decision Tree Lets compute the rest of probablities
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statistics and decision weighting schemes deal most effectively with the risks of minimising false positives? Which are the most effective for minimising false negatives? Which one(s) would you recommend if we had no information and cannot obtain reliable estimates for, costs, profits, or relative risks? Give examples of business problems where the risk of false positives and false negatives, respectively, are paramount. Different kind of modelling techniques such as Decision Tree or Logistic Regression
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