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The main focus of this seminar paper is on decision tree analysis and its applications in various industries. It also discusses about issues of decision making under uncertainty and risks involved in some of the projects.
Statement of the problem For successful execution of a project, a project manager should be able to take right decisions under conditions of certainty, risk and uncertainty. As the situation progresses from certainty to risk to uncertainty, the expected potential damage to the project increases.
Various methods of decision making are employed in order to take optimal decisions. The study of decision tree analysis is done to understand its significance in assisting project managers in taking decisions.
It does not provide in-depth knowledge of all techniques of decision making under uncertainty and risk. Review of literature Basics of decision tree analysis Decision tree is a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility.
Its common application is in operations research, especially in decision analysis, for identifying a strategy to attain an objective.
Other applications include its use as a descriptive means for calculating conditional probabilities. It acts as visual tool where the expected values or expected utility of competing alternatives are calculated and guides in choosing the best alternative.
Decision trees depict the sequence of interrelated decisions and the expected results of making choice among alternatives. When a decision is to be made, there are generally more than one choices or options.
The available choices are depicted in tree form starting at the left with the risk decision branching out to the right with possible outcomes. Decision trees are usually used for risk events associated with time or cost. A decision tree consists of 3 types of nodes: Decision nodes which are commonly represented by squares 2.
Chance nodes which are represented by circles 3. End nodes which are represented by triangles Decision tree is drawn from left to right and has splitting paths but no converging paths.
Therefore, in cases of elaborate future events, it is often difficult to draw manually. Nowadays various solutions and softwares are provided by many companies for drawing decision trees, analyzing the results and defining the best alternative amongst the available choices.
Steps in decision tree analysis Main steps in decision tree analysis are as follows: Identifying the problem and alternatives To understand the problem and develop alternatives, it is necessary to acquire information from different sources like marketing research, economic forecasting, financial analysis, etc.
As the decision situation unfolds, various alternatives may arise which are to be identified.
There would also be kinds of uncertainties in terms of market size, market share, prices, cost structure, availability of raw material and power, governmental regulation.
Technological change, competition, etc. Recognising that risk and uncertainty are inherent characteristics of investment projects, persons involved in analyzing the situation must be encouraged to express freely their doubts, uncertainties, and reservation and motivated to suggest contingency plans and identify promising opportunities in the emerging environment.
Delineating the decision tree The decision tree represents the anatomy of decision situation. It illustrates decision points along with the alternative options available for experimentation and action at these decision points chance points where outcomes are dependent on a chance process and the likely outcomes at these points This decision tree diagrammatically reflects the nature of decision situation in terms of alternative courses of action and chance outcomes which have been identified in the first step of the analysis.
If myriad possible future events and decisions are considered, it can become very complex and cumbersome. As a result, it would not be a useful tool of analysis.Apr 29, · Predicting Response at BookBinders: Decision Trees Recursive partitioning algorithms (or decision trees) are a versatile tool for uncovering patterns or relationships in data.
They are especially useful when there is a large set of potential predictors and when you are not sure which are most important or what the relationships between the predictors and the.
Quick Essay Solutions About Contact Cart. BUS Week 2 Assignment - Decision Analysis Case Study Decision Analysis Case Study: Valley of the Sun Reviews Based on the information presented in the case study, create a decision tree or Excel-based analysis to determine the most appropriate recommendation.
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. Question 3: An person has applied for positions at Company A, Company B, and Company C.
The probability of obtaining an offer from Company A is , from Company B is . Article analysis research paper decision tree. Essay internet of things your future write essay on myself zila parishad Essay globalization effect bangladesh My favorite dish essay township article review title vii essay immigration law deteriorating writing advice essay beginners.
Steps in essay writing letter jack london essay brisbane. Decision analysis. A final decision analysis project/assignment is required for the course using the material presented in class, supplemented by course lectures, in-class discussions, and .