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 | | Fundamental Concepts in the Design of Experiments by Charles R. Hicks, Kenneth V. Turner ISBN-10: 9780195122732 ISBN-10: 0-19-512273-9 ISBN-13: 9780195122732 ISBN-13: 978-0-19-512273-2 Hardcover 1999-03-25 Oxford University Press, USA Find Lowest Price |
Editorials | ||
Product Description Fundamental Concepts in the Design of Experiments, 5/e offers comprehensive coverage of the key elements of experimental design used by applied researchers to solve problems in the field. Wide-ranging and accessible, it shows students how to use applied statistics for planning, running, and analyzing experiments. Featuring over 350 problems taken from the authors' actual industrial consulting experiences, the text gives students valuable practice with real data and problem solving. The problems emphasize the basic philosophy of design and are simple enough for students with limited mathematical backgrounds to understand. The authors provide extensive coverage of the analysis of residuals, the concept of resolution in fractional replications, Plackett-Burman designs, and Taguchi techniques. SAS (Statistical Analysis System) computer programs are incorporated to facilitate analysis. Thoroughly revised and updated, this new edition includes sixty new problems, focuses more on computer use (adding computer outputs from statistical packages like Minitab, SPSS, and JMP), and emphasizes graphical procedures including residual plots and normal quantile plots. Ideal for various advanced undergraduate and graduate experimental methods courses taught in statistics, engineering, and mathematics departments, this book will also appeal to professionals and researchers doing experimental work. | ||
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. | ||
Statistics by example only - very little theory/concepts After using this book for a class, we all agreed that this book was not the best for those of us who are just learning the concepts in analyzing variance. The author tends to assume the basics are "hard-coded" into the students head. Fair enough. His next step, however, is not to discuss the theory/concept. Rather, it is to give an example of what he is talking about, hoping you will grasp the concept. It would very helpful to have the concepts explained and then the examples given. In addition, the notation (subscripts) are not always explained, nor are the formulas obvious/straightforward. Finally, the book has editing problems. A better editor and supplementary manuals (step-by-step explanation of concepts and formulas, SPSS instruction, etc.) would be a big help. My recommendation would be to find another book from which you will learn statistics. | ||