Executive Summary Merck & Company has been presented with an opportunity to invest $30 million for the purchasing rights of an obesity and high cholesterol lowering drug‚ KL-798 from Kappa Labs. Based on the expected probabilities of success through each product-development phase for this new drug‚ as well as the costs involved‚ the net present value of the project is -$1.16 million and is therefore recommended that Merck passes on the investment. Sensitivity analysis also show that adjusting
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Explain the parts of a decision tree. There are three parts of a decision tree. They are decision nodes (squares)‚ probability nodes (circles)‚ and decision alternatives (branches). 2.What are some benefits of using decision trees? Decisions trees force you to consider as many possible outcomes of a decision. They can provide the framework to consider the probability and payoffs of decisions‚ which can help one‚ analyze a decision to make the most inform decision possible. 3.In
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Should Merck license the compound? Merck would be responsible for 1) the approval of Davanrik 2) the manufacture of Danavrik 3) marketing of Danavrik Merck would pay LAB for 1) initial fee 2) royalty on all sales 3) make additional pymts as Danavrik completed each stage of approval process (3 Phases) Additional facts: approval process should take 7 years patent will cover 17 years (7 of approval process nad 10 yr period of exclusivity beginning in yr 7) 1 Assumptions:
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Should Merck license the compound? Merck would be responsible for 1) the approval of Davanrik 2) the manufacture of Danavrik 3) marketing of Danavrik Merck would pay LAB for 1) initial fee 2) royalty on all sales 3) make additional pymts as Danavrik completed each stage of approval process (3 Phases) Additional facts: approval process should take 7 years patent will cover 17 years (7 of approval process nad 10 yr period of exclusivity beginning in yr 7) 1 Assumptions: All Cash flows
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Decision Trees A Primer for Decision-making Professionals By Rafael Olivas 2007 Decision Trees A Primer for Decision-making Professionals ii Decision Trees A Primer for Decision-making Professionals Table of Contents Section Page Preface................................................................................................................................. iv 1.0 Introduction................................................................................................
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DECISION TREES DECISION Decision trees may be described as the graphic display of the decision-making process. Let us take for example a situation where one must decide whether to go to a movie house or to stay at home and watch TV or a video tape. State of nature node Branches Good movie Decision node Movies Bad Movie Good program TV New program or cassette Poor program Rerun
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10:35 AM Page 96 Chapter 4 DECISION ANALYSIS CONTENTS 4.1 PROBLEM FORMULATION Influence Diagrams Payoff Tables Decision Trees DECISION MAKING WITHOUT PROBABILITIES Optimistic Approach Conservative Approach Minimax Regret Approach DECISION MAKING WITH PROBABILITIES Expected Value of Perfect Information RISK ANALYSIS AND SENSITIVITY ANALYSIS Risk Analysis Sensitivity Analysis DECISION ANALYSIS WITH SAMPLE INFORMATION An Influence Diagram A Decision Tree Decision Strategy Risk Profile Expected
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Lab 1: Decision Trees and Decision Rules Evgueni N. Smirnov smirnov@cs.unimaas.nl August 21‚ 2010 1. Introduction Given a data-mining problem‚ you need to have data that represent the problem‚ models that are suitable for the data‚ and of course a data-mining environment that contains the algorithms capable of learning these models. In this lab you will study two well-known classification problems. You will try to find classification models for these problems using decision
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Maryland‚ USA Decision Analysis Publication details‚ including instructions for authors and subscription information: http://pubsonline.informs.org A Multiple-Objective Decision Analysis for Terrorism Protection: Potassium Iodide Distribution in Nuclear Incidents Tianjun Feng‚ L. Robin Keller‚ To cite this article: Tianjun Feng‚ L. Robin Keller‚ (2006) A Multiple-Objective Decision Analysis for Terrorism Protection: Potassium Iodide Distribution in Nuclear Incidents. Decision Analysis 3(2):76-93
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Homework 3 4. Discuss the benefits and drawbacks of a binary tree versus a bushier tree. The structure of binary is simple than a bushier tree. Each parent node only has two child. It save the storage space. Besides‚ binary tree may deeper than bushier tree. The result record of binary may not very refine. 5. Construct a classification and regression tree to classify salary based on the other variables. Do as much as you can by hand‚ before turning to the software. Data： NO. 1 2 3 4 5 6 7 8 9 10
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