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Management Science: The Art of Modeling with Spreadsheets Hardcover – October 26, 2010

ISBN-13: 978-0470530672 ISBN-10: 0470530677 Edition: 3rd

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Product Details

  • Hardcover: 528 pages
  • Publisher: Wiley; 3 edition (October 26, 2010)
  • Language: English
  • ISBN-10: 0470530677
  • ISBN-13: 978-0470530672
  • Product Dimensions: 8.7 x 0.9 x 11.1 inches
  • Shipping Weight: 2.6 pounds (View shipping rates and policies)
  • Average Customer Review: 3.9 out of 5 stars  See all reviews (16 customer reviews)
  • Amazon Best Sellers Rank: #479,985 in Books (See Top 100 in Books)

Customer Reviews

The explanations and walkthrough written in the book is not very helpful and have lots of gaps.
Mariano Apuya Jr
This textbook was required for a Information Systems class in Decision Modeling and both the students and the professor found it difficult to read.
Geekcheck
It looks completely new, probably only had one owner before me, or everyone was very careful with it.
pricrema

Most Helpful Customer Reviews

21 of 21 people found the following review helpful By Mariano Apuya Jr on July 30, 2011
Format: Hardcover
The title of the class I took with this book was called `Decision Models for Managers'. The book covers basic Excel from organizing spreadsheets to sorting, filtering data, and pivot tables. The introduction to modeling covers how to solve problems. The authors have a method where you structure problems by steps which include diagramming. I had a hard time with the method that they describe, it isn't really elegant. And the exercises for these are not very intuitive to solve. While management science requires high level math like linear algebra and third semester calculus, the math in this book is does not go beyond pre-calculus. The math skills that are needed are statistics, and not the advanced kind. If you understand when the p-value is significant, then there you go. This book is almost all about spreadsheets, but sadly, I did not become an Excel power user by studying the book.

A lot of topics are very amenable to spreadsheets-regression, moving average, exponential smoothing, and optimization. For forecasting methods such as moving average, it is intuitive to use =Average(lag 1, lag 2,....), the same goes for exponential smoothing . A hint on exponential smoothing-you will need to find the parameter alpha (and beta if including trend), you can use Excel's solver to find this by minimizing MSE. The way the authors teach is by doing sensitivity analysis and finding it by trial and error. Excel spits out a regression output for you, clickpath: Data-> Data Analysis-> Regression.

For the rest of the topics, you must use the Risk Solver Platform that comes with the book. There is no CD, there is a code in the front flap that is needed to install a trial version along with a code from the instructor.
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3 of 3 people found the following review helpful By Anonymous Customer on May 26, 2013
Format: Hardcover Verified Purchase
As a positive, this did provide a good level beyond "back of the envelope" calculations for Excel, which is commonly available, so that was somewhat useful. However, for general conceptual modeling (ie, visualizing it), it spoke more of modeling as being a fluid art (which I agree with) but didn't offer much in the way beyond a few quips of what experienced modelers do. I think this makes it predominantly task-oriented, which can be taken either as positive or negative depending on your needs. In any case, I think this should be seen as a supplementing skill rather than a standalone source.

Very little background should be necessary beyond the ability to understand basic equations. Excel does the math for you.
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3 of 3 people found the following review helpful By Fernando Borges on May 5, 2011
Format: Hardcover Verified Purchase
Definitely this very well written book takes you by hands so you can go perform your first steps towards the modeling and optimization art. Of course you need to burn out your brain in order to create your own model and its solutions, but the book give you the basis for the advanced levels in problem solving. If you are intending next step, try explore more about VBA so you can program different engine solvers like ant colony, simulated annealing, bats colony and so on.
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1 of 1 people found the following review helpful By Geekcheck on February 22, 2013
Format: Hardcover Verified Purchase
This textbook was required for a Information Systems class in Decision Modeling and both the students and the professor found it difficult to read. The problem lies in the author's habit of over-explaining simple concepts and deluging the reader with "fluff" information. This is especially true, when it comes to the work problems which usually lead off with information that doesn't relate to the important material needed to perform the calculations.

This is one of the few times, where too much information is a bad thing. The first two chapters of the book are probably the best as they explain how decision modeling is an "art form" and something that is more conceptually-based and uses Excel as a way to express itself. Unfortunately, the author quickly forgets this after Chapter 3 and dives headfirst into complex work problems, as if the reader has advanced knowledge of these concepts and a mastery of Excel.

The book seems to be designed for those who have more than a general knowledge of Excel and decision modeling. But as a teaching reference it is a poor choice for students.
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3 of 4 people found the following review helpful By Mark Harmon on September 21, 2012
Format: Hardcover Verified Purchase
As the author of Step-By-Step Optimization With Excel Solver and a college statistics instructor, I can definitely say that If you do any kind of deep optimization modeling with Excel, here's your book. Stephen Powell and Kenneth Baker have put together, by far, the most in-depth book on how to use Excel to scientifically analyze uncertainty in complicated business decisions. They not only present the theory but also provide clear, step-by-step instructions loaded with with screenshots of Excel in use. The book does a GREAT job at presenting very complicated material in a way that a reasonably proficient Excel user can comprehend without getting a headache. Some of the topics they cover are Monte Carlo simulation, Robust Optimization, Nonlinear Optimization using Excel's built-in Solver, Networking Models, Linear and Integer Programming in Excel, and combining Optimization with Simulation. No matter how much of a whiz-bang, quant jock in Excel you are, this book will take you to a new level of expertise in using the Excel Solver to model uncertainty in order to make better business decisions. I love stuff like this and thought it was fantastic. Those who want to be expert in optimization and risk analysis will really enjoy this book!
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Management Science: The Art of Modeling with Spreadsheets
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