Neuware - A comprehensive overview of experimental design at the advanced levelThe development and introduction of new experimental designs in the last fifty years has been quite staggering and was brought about largely by an ever-widening field of applications. Design and Analysis of Experiments, Volume 2: Advanced Experimental Design is the second of a two-volume body of work that builds upon the philosophical foundations of experimental design set forth half a century ago by Oscar Kempthorne, and features the latest developments in the field.Volume 1: An Introduction to Experimental Design introduced students at the MS level to the principles of experimental design, including the groundbreaking work of R. A. Fisher and Frank Yates, and Kempthorne s work in randomization theory with the development of derived linear models. Design and Analysis of Experiments, Volume 2 provides more detail about aspects of error control and treatment design, with emphasis on their historical development and practical significance, and the connections between them. Designed for advanced-level graduate students and industry professionals, this text includes coverage of:Incomplete block and row-column designsSymmetrical and asymmetrical factorial designsSystems of confoundingFractional factorial designs, including main effect plansSupersaturated designsRobust design or Taguchi experimentsLattice designsCrossover designs In order to facilitate the application of text material to a broad range of fields, the authors take a general approach to their discussions. To aid in the construction and analysis of designs, many procedures are illustrated using Statistical Analysis System (SAS�) software.

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T�tulo: Design and Analysis of Experiments, Volume 2 : Advanced Experimental Design
Editor: Wiley Apr 2005
Fecha de publicaci�n: 2005
Idioma: Ingl�s
ISBN 10: 0471551775
ISBN 13: 9780471551775
Encuadernaci�n: Buch
Estado: Neu
Dimensiones: 240�mil�metros de ancho por 161 de alto por 48 de largo
Peso: 1370 gramos

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The development and introduction of new experimental designs in the last fifty years has been quite staggering, brought about largely by an ever-widening field of applications. Design and Analysis of Experiments, Volume 2: Advanced Experimental Design is the second of a two-volume body of work that builds upon the philosophical foundations of experimental design set forth by Oscar Kempthorne half a century ago and updates it with the latest developments in the field. Designed for advanced-level graduate students and industry professionals, this text includes coverage of incomplete block and row-column designs; symmetrical, asymmetrical, and fractional factorial designs; main effect plans and their construction; supersaturated designs; robust design, or Taguchi experiments; lattice designs; and cross-over designs.

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KLAUS HINKELMANN, PHD, is Emeritus Professor of Statistics at Virginia Polytechnic Institute and State University Department of Statistics, where he also served as both graduate administrator and department head. In addition to being a Fellow of both the American Statistical Association and the American Association for the Advancement of Science, Professor Hinkelmann is a member of the International Statistical Institute, and has served as a council member of the International Biometric Society. He was editor of Biometrics and the Current Index to Statistics.

OSCAR KEMPTHORNE, SCD, was Emeritus Professor of Statistics and Emeritus Distinguished Professor of Liberal Arts and Sciences at Iowa State University. He was a Fellow of the American Statistical Association, the Institute of Mathematical Statistics, and the American Association for the Advancement of Science, as well as an Honorary Fellow of the Royal Statistical Society and a member of the International Statistical Institute. In addition, Dr. Kempthorne was a past president of the Eastern North American Region (ENAR) of the International Biometric Society, a former chairman of statistics within the American Association for the Advancement of Science, and a past president of the Institute of Mathematical Statistics.

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