Design and Analyse Your Experiment with Minitab
Hodder Arnold (Publisher)
Published on 23. February 2007
Book
Paperback/Softback
288 pages
978-0-340-80780-4 (ISBN)
Article exhausted; check for reprint
Description
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.>
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
John Wiley and Sons Ltd
Target group
College/higher education
Professional and scholarly
Illustrations
Illustrations
Dimensions
Height: 245 mm
Width: 189 mm
Thickness: 16 mm
Weight
680 gr
ISBN-13
978-0-340-80780-4 (9780340807804)
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Schweitzer Classification
Other editions
New editions

Tony Greenfield | Andrew V. Metcalfe
Design and Analyse Your Experiment Using MINITAB
Book
02/2007
1st Edition
Wiley
€60.50
Shipment within 10-20 days
Persons
Tony Greenfield is an Industrial Research Consultant. Andrew Metcalfe is a Senior Lecturer in Statistics at the University of Adelaide.
Content
Preface. Notation. Style. Website for data sets. Sources of data. Guide. Descriptive statistics and plotting. Single sample experiments. Comparison of proportions. Comparing two treatments. Comparison of several means. Two-level factorial experiments. Fractional two-level factorial experiments. Response surfaces. Hill climbing. Robust design. Hierarchical (nested) designs. Two factors at several levels. Crossed and nested factors, and split plot designs. Mixture designs. Discrete response. Post-script. The authors. Glossary. References. Index.