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Johannes Ledolter (University of Iowa) and Arthur J. Swersey (Yale University):

Testing 1 – 2 – 3: Experimental Design with Applications in Marketing and Service Operations, published by Stanford University Press, 2007.

Further information can be found on the web link

Table of Contents

Chapter 1: Introduction
Chapter 2: A Review of Basic Statistical Concepts
Chapter 3: Testing Differences among Several Means: Completely Randomized and Randomized Complete Block Experiments
Chapter 4: Two-Level Factorial Experiments
Chapter 5: Two-level Fractional Factorial Designs
Chapter 6: Plackett-Burman Designs
Chapter 7: Experiments with Factors at Three or More Levels
Chapter 8: Non-orthogonal Designs and Computer Software for Design Construction and Data Analysis
Appendix: Thirteen Cases
Eagle Brands
Magazine Price Test
Mother Jones (A)
Peak Electronics: The Broken Tent Problem (A)
Office Supplies e-mail Test
Mother Jones (B)
Peak Electronics: The Broken Tent Problem (B)
Experiments in Retail Operations: Design Issues and Application
Experimental Design on the Front Lines of Marketing: Testing New Ideas
Piggly-Wiggly
United Dairy Industries
Almquist & Wyner
PhoneHog

A brief description and a summary of the target audience are enclosed. We are excited as we believe that this is one of the first design books with a focus on business problems.

Brief description

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.

Target audience

• Undergraduate business and MBA students desiring an introduction to the statistical design of experiments and their use in business.
• Quality professionals and quality consultants involved in training and implementation of Six Sigma and other quality programs.
• Business professionals and management consultants (especially in marketing and operations) involved with the design and analysis of experiments, as well as those who want to learn and apply these practical tools to the problems they face.
• Undergraduate and graduate engineering students and professional engineers interested in the design of experiments.
• Undergraduate and graduate statistics students wishing to learn about design of experiments and their use in business and engineering.
• Undergraduate and graduate students preparing for careers in quality management.

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