Quantitative Methods for Business
Language: English
Pages: 936
ISBN: 1285866312
Format: PDF / Kindle (mobi) / ePub
You don't have to be a mathematician to maximize the power of quantitative methods. Written for the current?or future?business professional, QUANTITATIVE METHODS FOR BUSINESS, 13E makes it easy for you to understand how you can most effectively use quantitative methods to make smart, successful decisions. The book's hallmark problem-scenario approach guides you step by step through the application of mathematical concepts and techniques. Memorable real-life examples demonstrate how and when to use the methods found in the book, while instant online access provides you with Excel worksheets, LINGO, and the Excel add-in Analytic Solver Platform. The chapter on simulation includes a more elaborate treatment of uncertainty by using Microsoft Excel to develop spreadsheet simulation models. The new edition also includes a more holistic approach to variability in project management. Completely up to date, QUANTITATIVE METHODS FOR BUSINESS, 13E reflects the latest trends, issues, and practices from the field.
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Important contribution to the decision-making process. When those familiar with the problem agree that it has been adequately structured, work can begin on developing a model to represent the problem mathematically. Solution procedures can then be employed to find the best solution for the model. This best solution for the model then becomes a recommendation to the decision maker. The process of developing and solving models is the essence of the quantitative analysis process. Model Development.
Are sometimes called random experiments. 2.2 2.2 31 Assigning Probabilities to Experimental Outcomes Assigning Probabilities to Experimental Outcomes With an understanding of an experiment and the sample space, let us now see how probabilities for the experimental outcomes can be determined. The probability of an experimental outcome is a numeric measure of the likelihood that the experimental outcome will occur on a single repetition of the experiment. In assigning probabilities to.
Posterior probabilities of each disease for the following medical findings. a. b. c. d. The patient has symptom S1. The patient has symptom S2. The patient has symptom S3. For the patient with symptom S1 in part (a), suppose that symptom S2 also is present. What are the revised probabilities of D1 and D2? 27. Recently, management at Oak Tree Golf Course received a few complaints about the condition of the greens. Several players complained that the greens are too fast. Rather than react to the.
Chapter do not by themselves make decision recommendations, they do provide assistance to the decision maker in terms of understanding the uncertainties inherent in the problem. Ultimately, this better understanding may lead to new and better decisions. Glossary Random variable A numeric description of the outcome of an experiment. Discrete random variable A random variable that may assume only a finite or infinite sequence of values. Continuous random variable A random variable that may assume.
Used—management science (MS), operations research (OR), decision science and business analytics—are often used interchangeably. The scientific management revolution of the early 1900s, initiated by Frederic W. Taylor, provided the foundation for the use of quantitative methods in management. However, modern research in the use of quantitative methods in decision making, for the most part, originated during the World War II period. At that time, teams of people with diverse specialties (e.g.,.