Testing 1 - 2 - 3: Experimental Design with Applications in Marketing and Service Operations

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This book is about the power of statistical experiments. In the past, books on experimental design focused almost entirely on manufacturing problems. In contrast, although this book is relevant to manufacturing and includes useful examples in that area, its emphasis is on applications to marketing and service operations. The authors provide a fresh and practical treatment of the key topics in designing and analyzing experiments. Testing in the business world is commonplace, and the usual approach is to change one factor at a time while holding other factors constant. This approach may seem logical and appealing, but, as the authors explain, it is highly inefficient, and may lead to wrong conclusions. The better method, the authors propose, is to test all factors simultaneously. Doing so not only reduces the costs of experimenting but also provides the decision-maker with better information.

Throughout the book, the authors illustrate concepts with practical examples. In addition, the book includes a set of 13 separate real-world cases based on the actual implementation of experimental design methods.

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Editorial Reviews

From the Publisher
"This is the first book which is particularly devoted to applications of experimental design in marketing, service operations and general business problems. he authors give an easy to read non-technical treatment of full and fractional factorial designs supplemented by 13 cases."—Austrian Journal of Statistics

"Ledolter and Swersey succeed in conveying their passion for experimental design and sharing the power and practical value of these methods. The real-world examples used in the book are excellent."—Bovas Abraham, University of Waterloo

"The authors present a wealth of interesting examples, many of which come from marketing, to minimize mathematical formalism and to help students learn how experimental design methods work and why they are so potentially useful. At last we have an accessible and relevant resource to learn about these powerful ideas."—Bert Gunter, Principal Biostatistician, Genentech

"Ledolter and Swersey bring the powerful methodology of statistically designed experiments to the market researcher and service systems analyst. They provide a wealth of detailed real world examples, share many practical insights, and provide just the right amount of theory so that the methods can be understood and used properly. This is an empowering book." —Peter Kolesar, Professor Emeritus, Columbia Business School

"The authors are to be commended for their presentation of an eminently readable text that broadly—yet thoroughly—exposes marketers to statistical experimentation. The marketing practitioner will find case studies that amply demonstrate the benefits of the experimental approach. The marketing researcher will find assured guidance on how to design, execute, and analyze experiments of some complexity. This unique combination makes it a timely, important, and highly recommended text." —Martin Koschat, International Institute for Management Development

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Product Details

  • ISBN-13: 9780804756129
  • Publisher: Stanford University Press
  • Publication date: 5/1/2007
  • Edition description: 1
  • Pages: 312
  • Sales rank: 1,170,299
  • Product dimensions: 7.00 (w) x 10.00 (h) x 1.00 (d)

Meet the Author

Johannes Ledolter is the C. Maxwell Stanley Professor of Management Sciences at the University of Iowa, and Professor of Statistics at the Vienna University of Economics and Business Administration. His books include Introduction to Regression Modeling (with Bovas Abraham) and Achieving Quality Through Continual Improvement (with Claude W. Burrill). Arthur J. Swersey is Professor of Operations Research at the Yale School of Management.

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Table of Contents

Preface     ix
Introduction     1
A Review of Basic Statistical Concepts     8
Testing Differences Among Several Means: Completely Randomized and Randomized Complete Block Experiments     47
Two-Level Factorial Experiments     64
Two-Level Fractional Factorial Designs     111
Plackett-Burman Designs     150
Experiments with Factors at Three or More Levels     169
Nonorthogonal Designs and Computer Software for Design Construction and Data Analysis     192
Case Studies     213
References     289
Index     295
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