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Quantitative Analysis for Management Hardcover – 2 Feb 2005


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Product details

  • Hardcover: 752 pages
  • Publisher: Prentice Hall; 9 edition (2 Feb. 2005)
  • Language: English
  • ISBN-10: 0131857029
  • ISBN-13: 978-0131857025
  • Product Dimensions: 21 x 3.3 x 26.4 cm
  • Average Customer Review: 2.5 out of 5 stars  See all reviews (2 customer reviews)
  • Amazon Bestsellers Rank: 1,550,087 in Books (See Top 100 in Books)
  • See Complete Table of Contents

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Most Helpful Customer Reviews

Format: Hardcover Verified Purchase
It was a bargain to buy. The book had traces of use, but nothing major and overall the condition was satisfactory! Nice with a retailer who will send to DK.
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0 of 2 people found the following review helpful By Rachel Cassidy on 17 Feb. 2014
Format: Hardcover Verified Purchase
The book is in good condition but did not come with the CD software (which it is advertised as having) what is the point?! Disappointed and have contacted seller.
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Most Helpful Customer Reviews on Amazon.com (beta)

Amazon.com: 14 reviews
11 of 11 people found the following review helpful
Introduction 17 Dec. 2006
By H. Sætra - Published on Amazon.com
Format: Hardcover
We used this book in my "Operations analysis"-class, and it's a great introduction to the subjects discussed. Some very basic probability for estimating values and descision theory. Some regression in addition to other forecasting methods. Good sections on linear and integer programming, and also basic queuing models. Markov analysis is about as far as this book goes, and it basically just touches upon all the subjects in order to make the reader grasp the basic ideas.

One minus is the Windows-only software, no Mac-support there, but that only meant that I had to use Excel, which imo helped me gain a better understanding of the subjects, as I had to formulate all the spreadsheets myself instead of just feeding numbers into the QM-package, which imo seems like a total waste of a chance to learn. Anyway, most areas are covered with respect to both QM and Excel, which makes the non-existant Mac-support bareable.
13 of 14 people found the following review helpful
Excellent introduction to the subject 28 Feb. 2006
By Kimberly - Published on Amazon.com
Format: Hardcover
I read this book as the assigned text for a course in Quantitative Analysis and found it to be an excellent text for such a class. Each Model and equation presented is explained through realistic examples, illustrations, and explanations of the math. This made the subject very easy to comprehend and apply to the real world.

Exercises at the end of each chapter are also based on real-world situations and case studies are included in the book and the CD that go into more detail about a real world use for each model.

The book was also easy to read and not overly technical when explaining mathematic concepts. An excellent text for an introduction to the field of management science.
20 of 24 people found the following review helpful
Great Book 12 Dec. 2001
By "tlcookacct" - Published on Amazon.com
Format: Hardcover
I had one of the worst instructors on the planet this semester. I literally had to teach myself this entire course.
This book made it so much easier. Great diagrams, simple explanations. I ended up with an A.
19 of 23 people found the following review helpful
Easy to follow 17 Sept. 2000
By A Customer - Published on Amazon.com
Format: Hardcover
This book is easy to follow and the included cd makes solving the problems easy. It also has online links for each chapter.
3 of 3 people found the following review helpful
Uses Excel as a modeling shell 24 Jan. 2011
By Herbert L Calhoun - Published on Amazon.com
Format: Hardcover
This volume focuses on the application of mathematical models for business decision-making. It covers the traditional topics in the traditional way, with a few notable exceptions. For instance, its lessons are customizable using an attached computer disc with the algorithms of most of the techniques programmed as Excel models (but only usable on a PC utilizing a Windows operating system). Mac users, like myself, must program the book's algorithms in Excel and save them in separate computer files.

Although the book offers a competent set of presentations, it is light on mathematical development and falls short of giving inventive students a "leg up" (or enough to do) in going beyond the "practice examples" presented in the text.

As but one example, the excellent section on forecasting stops short at "Adaptive Forecasting," leaving the details to be worked out by the reader. In effect, leaving the reader holding the bag with a single statement to the effect that if a signal passes a preset limit, then the exponential smoothing constants will be selected to minimize forecasting errors, and then adjusted accordingly? (Well thanks a lot.)

It would have been much more useful to either give a few examples as was done in all the other cases, or refer us to more advance sources where the reader could investigate the technique further on his own. The worse of all possibilities was to leave us with the hint that there is a better technique, but fail to share with us how this technique worked?

While the explanations throughout are excellent and always painfully clear, one gets the impression that the text itself also is a minimalist effort. Thus, except for using Excel as a modeling shell, there is not much more that can be recommended for these author's approach. Three stars.
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