Fundamental Concepts in the Design of Experiments

By Charles Robert Hicks

This brief, yet comprehensive text covers the essentials of experimental design used by applied researchers in solving problems in the field. It is appropriate for a variety of experimental methods courses found in engineering and statistics departments. Students learn to use applied statistics for planning, running, and analyzing an experiment. The text includes 350+ problems taken from the author's actual industrial consulting experiences to give students valuable practice with real data and problem solving. The use of the computer is promoted and SAS (Statistical Analysis System) computer programs are incorporated to facilitate analysis. Coverage of the analysis of residuals, the concepts of resolution in fractional replications, the Plackett-Burman designs, and Taguchi techniques is new to this edition.

• Format: Hardcover
• Language: English
• ISBN: 003097710X
• ISBN13: 9780030977107
• Release Date: January 1994
• Publisher: Oxford University Press
• Length: 68 Pages
• Weight: 2.00 lbs.
• Dimensions: 9.6" x 1.0" x 6.5"

Customer Reviews

Fundamental Concepts in the Design of Experiments

This book is very valuable for those actively engaged in the conduct of experiments, either operational or developmental in nature. It does require someone with a background in statistical methods using analysis of variance. The user needs to have a good understanding of statistical inference. There are many good working models of various analytic procedures provided.

Excellent, if you already know theoretical statistics

This book is written for people who already know the theory of statistics and want to do statistic consulting. The author begins with the basics of design of experiments: experiment, design and analysis. Then a brief (lovely) review of statistical inference follows; including: Estimation, test of hypothesis, power function and some easy applications. In the following chapters almost all statistical methods are presented; among others: single factor experiments, randomized block and latin square, factorial experiments, nested, experiments of two or more factors, 2^f -, 3^f factorials, split plot design, Taguchi, regression and finally miscellaneous topics including covariance analysis, response-surface experimentation and more. After each chapter there are problems and answers to odd-numbered problems can be found at the end of the book. Included is a practical summery with all methods presented in one table. Additionally you find a glossary of terms used in statisics, statistical tables and an index.The examples in the book are analysed using SAS. Knowing that S-Plus is much easier to handle (and knowing that SAS is frequently used in the industry), this is very useful. The mathematics used is easy, but - as mentioned in the preface - the fundamental concepts of statistical inference must be known.