Easy to understand-even for learners with limited math backgrounds, this book uses a modeling approach to provide thorough coverage of the basic techniques in quantitative methods and focuses on the managerial applications of these techniques. An interesting and reader friendly writing style makes for a clear presentation, complete with all the necessary assumptions and mathematical details. Chapter topics include probability concepts and applications, decision models and decision trees, regression models, forecasting, inventory control models, linear programming modeling applications and computer analyses, network models, project management, simulation modeling, and more. For an introduction toquantitative analysis, quantitative management, operations research, or management science-especially for those individuals preparing for work in agricultural economics and health care fields.
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This easy-to-use text provides students with the skills to apply the techniques of quantitative analysis in all kinds of organizational decision-making situations. Designed for optimum teaching flexibility, it covers every major topic in the quantitative analysis/management science field, showing how each technique works, discussing the assumptions and limitations of the models, and illustrating the real-world usefulness of each technique with many applications in both profit-making and nonprofit organizations. Dramatically revised, the Sixth Edition now offers a completely new look and feel to make teaching more efficient and enhance students' learning experience.
This best-selling volume has long been considered one of the most user accessible books for management science. The new edition retains and updates the traditional, comprehensive coverage of past editions but now adds spreadsheet-based problem solutions to most chapters. In addition, the book is now packaged with free software. The authors provide a comprehensive introduction to quantitative analysis, probability concepts and applications and decision theory models, as well as forecasting, control models, linear programming models and applications, transportation and assignment models, integer programming, goal programming, nonlinear programming, and branch and bound models, network models, project management, lines and queuing theory models and statistical quality control. For those interested in a comprehensive, yet accessible presentation of QM for management.
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