Decision Trees The Decision Tree module in Excel OM (and in POM for Windows) acts differently than all other modules because rather than creating a table of data it creates a graphical tree. We will use Example 3 in Chapter A5 from Heizer & Render’s Operations Management textbook for our example. After selecting the Decision Tree Module the screen will appear as in Figure 1 below. Figure 1: The Initial Decision Tree Screen Notice the Decision Tree Creation Window on the right. This is used
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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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15.0% 0 #NAME? #NAME? Depression Don't Test #NAME? -$40,000,000.00 Indications #NAME? #NAME? 0 #NAME? #NAME? Test Effective #NAME? -$150,000,000.00 #NAME? 75.0% -100,000,000 #NAME? #NAME? Test Merck Decision Tree Although a decision analysis would recommend that Merck not commit to the proposal, the company's balance sheet shows that it has significant assets to support a loss. The projected values of earning for depression and dual indications seem to be worth the
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DECISION TREE Nurse Delegation to Nursing Assistive Personnel (NAP) Step One – Assessment and Planning Are there laws and rules/regulations in place that support the delegation? [NMAC 16.12.2] Yes Is the task within the scope of practice of the delegating nurse? [NMAC 16.12.2] Yes Has there been assessment of the client’s needs? Yes No Do not delegate. No If not in the licensed nurse’s scope of practice, he/she should not delegate to NAP. Authority to delegate varies from state-to-state; licensed
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Los cinco patrones básicos de la mayoría de las series de tiempo aplicables a la demanda son: 1. Horizontal. La fluctuación de los datos en torno de una media constante. 2. Tendencia. El incremento o decremento sistemático de la media de la serie a través del tiempo. 3. Estacional. Un patrón repetible de incrementos o decrementos de la demanda, dependiendo de la hora del día, la semana, el mes o la temporada. 4. Cíclico. Una pauta de incrementos o decrementos graduales y menos previsibles de
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HKU552 XIANGHUA LU DAQIING ZHENG E-BUSINESS TRANSFORMATION AT ME-ONLINE The development of Shanghai Me Mechanical and Electrical Equipment Chain Co. Ltd. (SHMEC), a traditional mechanical and electrical equipment distribution company, mirrored the agony and frustration experienced by many other small and medium-sized enterprises operating during China’s socio-economic transformation process, particularly as it faced the challenge brought by information technology. The company’s growth parallels
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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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Decision Tree Gerber Product Company A. Background of the Company: Gerber was founded in 1927 in Fremont, Michigan by Daniel Frank Gerber, owner of the Fremont Canning Company, which produced canned fruit and vegetables. At the suggestion of a pediatrician, Gerber's wife Dorothy Gerber began making hand-strained food for their seven-month-old daughter, Sally. Recognising a business opportunity, Gerber began making baby food. By 1928 he had developed five products for the market and six
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www.palgrave-journals.com/thr Using decision trees to identify tourism stakeholders: The case of two Eastern North Carolina counties Erick T. Byrd* and Larry Gustke Received (in revised form): 1st May, 2006 *Department of Recreation, Tourism, and Hospitality Management, The University of North Carolina at Greensboro, PO Box 26170, Greensboro, NC 27402, USA Tel: + 1 336-334-3041; Fax: + 1 336-334-3238; E-mail: etbyrd@uncg.edu Erick T. Byrd is an Assistant Professor in the Department of Recreation
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Angoss predictive analytics to increase revenue, increase sales productivity and improve marketing effectiveness, while also reducing risk and cost. 2. Discuss on data preparation features provided by the product. Known for its industry, Decision Tree patent and a graphical user interface wizard driven which, Knowledge STUDIO is a modeling and predictive analysis workbench for advanced high-performance business analysts and quantitative analysts who offer a robust set of capabilities for the
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