Optimal Design of Experiments: A Case Study Approach

by Peter Goos, Bradley Jones

"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery , Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings."
― Christopher J. Nachtsheim , Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota  This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.

304 pages, Hardcover

First published June 13, 2011

Reviews

[Jacek · Rating 5 out of 5]

I wish there were more statistics books like this one. The authors' experience with real-life projects can be seen for a major part. For a practicing statistican it should be certainly complemented by a more rigorous textbook, but certainly serves as an excellent exposition to modern DOE.

[Dries · Rating 5 out of 5]

Goed verdiepend boek over design of experiments. Vereist voorkennis, niet helder op de basis

[Sanne Roever · Rating 5 out of 5]

Very nice book that explains some advanced topics using computer generated optimal designs. Optimal designs seem the way to, as these encompass classical designs to a large degree.

[Noshgul · Rating 4 out of 5]

This is a decent introduction to the optimal DOE. The writing style is somewhat special, half of the text consists of case studies written as a conversation between statistical consultant. This is on one hand a drawback of the book (it makes the book somewhat more lengthy than it could've been), on the other hand is the book somewhat more pleasant to read. After each case study a short overview is given of the involved mathematical methods, however this is not a proof based book. A nice addition is that for every chapter there is an overview of the current research/reference texts. In conclusion it will probably never become a classic reference like Agresti or Gelman et al. but it's a nice book to use in a first DOE class.