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Introduction to Business Analytics Using Simulation ModelsBy Dr Jonathan P Pinder PhD
Download PDF Introduction to Business Analytics Using Simulation ModelsBy Dr Jonathan P Pinder PhD
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Introduction to Business Analytics Using Simulation Models introduces the fundamental principle of business analytics and data science: APPLIED PROBABILITY. Because probability is extremely counter-intuitive, the book makes extensive use of simulation models to provide students with experiential learning to develop a deep and true understanding of how uncertainty and decision-making work. This book helps you understand the foundation of data science techniques in use today. Based on an MBA course Jon has taught at Wake Forest University over the past 25 years, Introduction to Business Analytics Using Simulation Models provides examples of real-world business problems to illustrate these principles. You’ll learn how to think about the uncertain future and create data-science probability models for business decision-making.
- Sales Rank: #507534 in Books
- Published on: 2015-08-06
- Original language: English
- Number of items: 1
- Dimensions: 9.25" h x .74" w x 7.50" l,
- Binding: Paperback
- 328 pages
About the Author
Jonathan P. Pinder is an Associate Professor of Management at Wake Forest University in Winston-Salem, North Carolina. He earned a BS in Civil Engineering at North Carolina State University and a Ph.D. in Business Administration at the University of North Carolina at Chapel Hill. Dr. Pinder's research interests include, business analytics, revenue management, stochastic optimization, nonlinear dynamical systems, resource allocation, and inventory management models. He has published articles in numerous journals including: Decision Sciences, Journal of Operations Management, The Journal of the Operational Research Society, Journal of Forecasting, Journal of Business and Economics, and Managerial and Decision Economics. He has received more than a dozen teaching awards and has 25 years of teaching and industry consulting experience.
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