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Statistical Analysis of Designed Experiments, Third Edition
von Shalabh, Helge Toutenburg
Verlag: Springer New York
Reihe: Springer Texts in Statistics
Hardcover
ISBN: 978-1-4899-8339-8
Auflage: 3rd ed. 2009
Erschienen am 30.10.2014
Sprache: Englisch
Format: 235 mm [H] x 155 mm [B] x 34 mm [T]
Gewicht: 949 Gramm
Umfang: 636 Seiten

Preis: 160,49 €
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Klappentext
Inhaltsverzeichnis

This book is the third revised and updated English edition of the German textbook \Versuchsplanung und Modellwahl" by Helge Toutenburg which was based on more than 15 years experience of lectures on the course \- sign of Experiments" at the University of Munich and interactions with the statisticians from industries and other areas of applied sciences and en- neering. This is a type of resource/ reference book which contains statistical methods used by researchers in applied areas. Because of the diverse ex- ples combined with software demonstrations it is also useful as a textbook in more advanced courses, The applications of design of experiments have seen a signi?cant growth in the last few decades in di?erent areas like industries, pharmaceutical sciences, medical sciences, engineering sciences etc. The second edition of this book received appreciation from academicians, teachers, students and applied statisticians. As a consequence, Springer-Verlag invited Helge Toutenburg to revise it and he invited Shalabh for the third edition of the book. In our experience with students, statisticians from industries and - searchers from other ?elds of experimental sciences, we realized the importance of several topics in the design of experiments which will - crease the utility of this book. Moreover we experienced that these topics are mostly explained only theoretically in most of the available books.



Comparison of Two Samples.- The Linear Regression Model.- Single#x2013;Factor Experiments with Fixed and Random Effects.- More Restrictive Designs.- Incomplete Block Designs.- Multifactor Experiments.- Models for Categorical Response Variables.- Repeated Measures Model.- Cross#x2013;Over Design.- Statistical Analysis of Incomplete Data.


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