The Science of Decision Making: A Problem-Based Introduction Using Excel, is a comprehensive, coherent, problems-based approach to learning the science of decision-making. It includes models of operations research for engineering, management, ecomomics and the sciences.
Intended for undergraduate and master's level students in engineering, management, economics, and the sciences taking courses in Operations Research, Introduction to Deterministic and Stochastic Methods, Management Science, Linear Programming, and Probabilistic Models.
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Educated at Princeton and Northwestern Universities, Eric V. Denardo worked for AT&T and The Rand Corporation before joining the faculty of Yale University. His work is noted for its breadth, innovation, and elegance.
Learn how to model and solve real decision-making problems using Excel.
This book is a practical, accessible, engaging, and deeply penetrating introduction to the science of decision making. It is a successful fusion of problem-based learning and spreadsheet computation with decision science. It surveys the modfels of operations research and of probability.
As you work through the problems within the chapters, you will acquire a potent set of tools for solving problems, and you'll see how to make practical use of them. You will find examples from engineering, economics, finance, operations management, business, medical decision making, and the sciences. You will see how to use the methodology in a variety of academic disciplines and career paths.
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Learn how to model and solve real decision-making problems using Excel.
This book is a practical, accessible, engaging, and deeply penetrating introduction to the science of decision making. It is a successful fusion of problem-based learning and spreadsheet computation with decision science. It surveys the modfels of operations research and of probability.
As you work through the problems within the chapters, you will acquire a potent set of tools for solving problems, and you'll see how to make practical use of them. You will find examples from engineering, economics, finance, operations management, business, medical decision making, and the sciences. You will see how to use the methodology in a variety of academic disciplines and career paths.
Features:
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