This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.

Most of the classic DOE books were written before DOE software was generally available, so the technical level that they assumed was that of the engineer or scientist who had to write his or her own analysis software. In this practical introduction to DOE, guided by the capabilities of the common software packages, Paul Mathews presents the basic types and methods of designed experiments appropriate for engineers, scientists, quality engineers, and Six Sigma Black Belts and Master Black Belts. Although instructions in the use of Minitab are detailed enough to provide effective guidance to a new Minitab user, the book is still general enough to be very helpful to users of other DOE software packages. Every chapter contains many examples with detailed solutions including extensive output from Minitab.

Progress in engineering and the physical sciences, agriculture and the biological sciences, and to some extent social science, depends on experiments. The design of such experiments is crucial. If they are poorly designed they will be inefficient and may lead to misleading conclusions. Nevertheless, many investigators and researchers in industry and universities are expected to design and analyze their own experiments. Even if investigators do have access to statistical advice, they will be expected to have some basic knowledge of the issues. This book aims to help. Covering all the most commonly used designs of experiments, the methods and the potential pitfalls are described in clear English. The techniques are introduced with case studies of practical significance. The cases are based on real experiments but are described in the context of three fictitious organizations: an engineering company, SeaDragon; a pharmaceuticals and chemicals manufacturer AgroPharm; and the Department of Social Studies at the University of Erewhon. All technical terms are defined and the mathematical development is restricted to that which is needed to use MINITAB. To note: the text makes reference to the following URL: www.greenfieldresearch.co.uk/doe/data.htm. However, this URL has since been updated to the following: https://web.archive.org/web/20161117011155/http://www.greenfieldresearch.co.uk/doe/data.htm Please use this link to have access to the supplementary material.

This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.

This is the Minitab Manual to accompany Design and Analysis of Experiments, 8th Edition. The eighth edition of this best selling text continues to help senior and graduate students in engineering, business, and statistics-as well as working practitioners-to design and analyze experiments for improving the quality, efficiency and performance of working systems. The eighth edition of Design and Analysis of Experiments maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book. Continuing to place a strong focus on the use of the computer, this edition includes software examples taken from the four most dominant programs in the field: Design-Expert, Minitab, JMP, and SAS.

"The first principle [of science] is that you must not fool yourself, and you are the easiest person to fool." Richard P. Feynman This practical guide will teach you how to use Blind Analysis with Design of Experiments and Response Surface Methodology, so you can avoid fooling yourself. Written for engineers and scientists who are familiar with Design of Experiments and Minitab software, it is the first to cover the Blind Analysis aspect of DOE, which prevents the inadvertent bias-even your own-that can sometimes crop up in data analysis. Those new to the techniques will appreciate the brief introduction to Design of Experiments and Response Surface Methodology. You can then dive into the technical details behind Blind Analysis, including Triple Blind Studies. Two thorough examples complete the lesson, clearly demonstrating how to incorporate Blind Analysis into DOE/RSM, using the Minitab software package. Support materials are available online with data for the Minitab examples. Blind Analysis in Design of Experiments and Response Surface Methodology will prepare you to apply its powerful techniques to your work right away. Human nature is geared toward finding what we are looking for, instead of what's actually there. Add Blind Analysis to your toolbox, and you'll avoid fooling yourself, in your experiments.