Decision Trees Using TreePlan 16 16.1 TREEPLAN OVERVIEW TreePlan is a decision tree add-in for Microsoft Excel 2000–2010 (Windows) and Microsoft Excel 2004 & 2011 (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)
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"The Process of Analysis ̶ Diagrams and Trees" Decision analysis offers organization and direction for thinking methodically about challenging alternatives. Complexity‚ uncertainty‚ multiple intentions and numerous perspectives can lead to different best guesses. The policy analyst has several tools she or he can use to make hard decisions easier to make. Two of these tools are decision trees and influence diagrams. As the author notes‚ these problem-structuring methods are valuable in producing
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Questions for the Merck Case Create a decision tree for Merck. The 2 leftmost branches would identify the alternatives related to licensing Davarink (specifically license versus not to license). Next‚ if Merck decides to pursue license‚ they go into phase I which results in a success‚ or failure. Phase I success is followed by phase II where Merck has the opportunity to develop the drug to treat depression alone‚ weight loss alone‚ or both‚ or contemplate phase II failure. Finally phase
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Definitions ………………………………………..............9 4. Decision Tree (Manual)…………………………………..10 5. Decision Tree (WinQSB) ………………………………...11 6. Decision Tree Analysis …………………………………..12 7. Explanation of Decision Tree…………………………….13 8. Sensitivity Analysis - Probability of Research Success …14 9. Sensitivity analysis - Selling price of DSS……………....15 10. Utility Decision Tree………………………………….....16 11. Decision Tree Analysis for Utility…………………….....17 12. Utility
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Basic Concepts of Classification and Prediction 2.1.1 Definition 2.1.2 Classification vs. Prediction 2.1.3 Classification Steps 2.1.4 Issues of Classification and Prediction 2.2 2 2 Decision Tree Induction 2.2.1 The Algorithm 2.2.2 Attribute Selection Measures 2.2.3 Tree P 223T Pruning i 2.2.4 Scalability and Decision Tree Induction 2.3 Bayes Classification Methods 2.4 Rule Based Classification 2.5 Lazy Learners 2.6 2 6 Prediction 2.7 How to Evaluate and Improve Classification 2.1.1 Definition
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shows the decision tree. ii) As the decision tree shows‚ the preferred alternative is to accept the order and purchase the injection molder‚ with an expected pro¯ t of $154.4 thousand. Exercise 1.2. Arthrodax Company (con’t) i) Figure 4.2 shows the decision tree. ii) As the decision tree shows‚ the preferred alternative is to accept the order and purchase the cases‚ with an expected pro¯ t of $99.9 thousand. Exercise 1.3. Arthrodax Company (con’t) i) Figure 4.3 shows the decision tree. Note that
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expressed as after tax present values discounted to time zero‚ including capital expenditures At any point "failure‚" investment decision is to stop funding Assuming Standard deviation of 0.5 Using T= 7 years in Black-Scholes Valuation 2 Decision Tree See worksheet "Decision Tree" 3 Detailed description of Real Option Technique "First‚ using a decision tree‚ I came up with a simple expected value of $13‚980‚000...... Merck & Company: Evaluating A Drug Licensing Opportunity Should
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Management Science – Workshop 2: Case Study Recreational Properties 1. 1. Framing the Decision 2. Recreational Properties obtained a package of options to acquire three parcels that would allow them to develop a ski resort. The company paid €500‚000 for the package of options in June 2001. The options gave the company the right‚ but not the obligation‚ to acquire the three parcels at a (strike) price of €10 million in June 2002. 3. Furthermore‚ in order to develop the three parcels
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tax present values discounted to time zero‚ including capital expenditures At any point "failure‚" investment decision is to stop funding Assuming Standard deviation of 0.5 Using T= 7 years in Black-Scholes Valuation 2 Decision Tree See worksheet "Decision Tree" 3 Detailed description of Real Option Technique "First‚ using a decision tree‚ I came up with a simple expected value of $13‚980‚000 based on the costs to complete each phase‚ the probabilities
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MMS I 5 Site Selection: Where to Locate • Infrequent but important • Location criteria for manufacturing facility • being “in the right place at the right time” • Must consider other factors‚ especially financial considerations • Location decisions made more often for service operations than manufacturing facilities • Location criteria for service • access to customers Prof N. Balasubramanian • nature of labor force • labor costs • proximity to suppliers and markets • distribution and transportation
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