Items related to Excel Data Analysis: Modeling and Simulation
Synopsis
This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills-Data Analysis, Business Modeling, and Simulation of Complex Problems. The focus of the book is clearly on analysis of problems for decision making, yet detailed explanations regarding how to use Excel tools are provided. After many years of teaching and consulting, it is abundantly clear to me that for most students, a good example is worth its weight in gold. This book contains many excellent examples in each chapter, some simple and others more complex, and there is an abundance of exhibits to guide the student through the maze of steps necessary for each analysis.
The content is quite data presentation - the Feng Shui of spreadsheets, effective communication and collaboration, data preparation - import, scrub, manipulate data, data analysis - statistical descriptive, inferential, and predictive, Design of Experiments, modeling - deterministic, probabilistic, What-if, Scenarios, simulation - quantifying uncertainty, Monte Carlo Simulation, optimization - constrained, Linear Programming, non-linear models, Goal Seek.
Couple these features with detailed discussions of how to realistically organize and extract insight from complex problems, and I believe you have a unique educational combination in one book.
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From the Back Cover
This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills―Data Analysis, Business Modeling, and Simulation of Complex Problems. The focus of the book is clearly on analysis of problems for decision making, yet detailed explanations regarding how to use Excel tools are provided. After many years of teaching and consulting, it is abundantly clear to me that for most students, a good example is worth its weight in gold. This book contains many excellent examples in each chapter, some simple and others more complex, and there is an abundance of exhibits to guide the student through the maze of steps necessary for each analysis. The content is quite diverse: · data presentation ― the Feng Shui of spreadsheets, effective communication and collaboration · data preparation ― import, scrub, manipulate data · data analysis ― statistical methods: descriptive, inferential, and predictive, Design of Experiments · modeling ― deterministic, probabilistic, What-if, Scenarios · simulation ― quantifying uncertainty, Monte Carlo Simulation · optimization ― constrained, Linear Programming, non-linear models, Goal Seek · Couple these features with detailed discussions of how to realistically organize and extract insight from complex problems, and I believe you have a unique educational combination in one book.
About the Author
Dr. Guerrero is a professor at Mason School of Business at the College of William and Mary, in Williamsburg, Virginia. He teaches in the areas of decision making, statistics, operations and business quantitative methods. He has previously taught at the Amos Tuck School of Business at Dartmouth College, and the College of Business of the University of Notre Dame. He is well known among his students for his quest to bring clarity to complex decision problems. He earned a Ph.D. Operations and Systems Analysis, University of Washington and a BS in Electrical Engineering and an MBA at the University of Texas. He has published scholarly work in the areas of operations management, product design, and catastrophic planning. Prior to entering academe, he worked as an engineer for Dow Chemical Company and Lockheed Missiles and Space Co. He is also very active in consulting and executive education with a wide variety of clients-- U.S. Government, International firms, as well as many small and large U.S. manufacturing and service firms. It is not unusual to find him relaxing on a quiet beach with a challenging Excel workbook and an excellent cabernet.
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