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Robert Mee

A Comprehensive Guide to Factorial Two-Level Experimentation


2009. 2014. xxiii, 545 S. 235 mm
Verlag/Jahr: SPRINGER, BERLIN; SPRINGER NEW YORK; SPRINGER 2014
ISBN: 1-489-98270-1 (1489982701)
Neue ISBN: 978-1-489-98270-4 (9781489982704)

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With applications in virtually every quantitative field, the statistical design of experiments is a useful skill. Practitioners wanting to expand their repertoire will find this book a helpful guide, while examples from many fields give the book broad appeal.
This book contains the most comprehensive coverage available anywhere for two-level factorial designs.

The re-analysis of 50 published examples serves as a how-to guide for analysis of the many types of full factorial and fractional factorial designs.

By focusing on two-level designs, this book is accessible to a wide audience of practitioners who use planned experiments.
Full Factorial Designs.- to Full Factorial Designs with Two-Level Factors.- Analysis of Full Factorial Experiments.- Common Randomization Restrictions.- More Full Factorial Design Examples.- Fractional Factorial Designs.- Fractional Factorial Designs: The Basics.- Fractional Factorial Designs for Estimating Main Effects.- Designs for Estimating Main Effects and Some Two-Factor Interactions.- Resolution V Fractional Factorial Designs.- Augmenting Fractional Factorial Designs.- Fractional Factorial Designs with Randomization Restrictions.- More Fractional Factorial Design Examples.- Additional Topics.- Response Surface Methods and Second-Order Designs.- Special Topics Regarding the Design.- Special Topics Regarding the Analysis.- Appendices and Tables.- Upper Percentiles of t Distributions, t.- Upper Percentiles of F Distributions, F.- Upper Percentiles for Lenth t Statistics, and.- Computing Upper Percentiles for Maximum Studentized Residual.- Orthogonal Blocking for Full 2 Factorial Designs.- Column Labels of Generators for Regular Fractional Factorial Designs.- Tables of Minimum Aberration Regular Fractional Factorial Designs.- Minimum Aberration Blocking Schemes for Fractional Factorial Designs.- Alias Matrix Derivation.- Distinguishing Among Fractional Factorial Designs.
Statistical design of experiments is useful in virtually every quantitative field. Two-level factorial designs, which are the focus of this book, provide the most efficient plans for exploring the effects of many factors at once. Engineers, physical scientists, and all who conduct experiments will find this book indispensible. The analysis of 50 published experiments from diverse fields gives the book broad appeal.