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＜電子ブック＞
Experimental Designs: Exercises and Solutions / by D. G. Kabe, Arjun K. Gupta

版	1st ed. 2007.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2007
本文言語	英語
大きさ	VIII, 300 p. 3 illus : online resource
著者標目	*Kabe, D. G author Gupta, Arjun K author SpringerLink (Online service)
件　名	LCSH:Statistics  FREE:Statistical Theory and Methods
一般注記	Theoretical Results -- Exercises -- Solutions This volume provides a collection of exercises together with their solutions in design and analysis of experiments. The theoretical results, essential for understanding, are given first. These exercises have been collected during the authors teaching courses over a long period of time. These are particularly helpful to the students studying the design of experiments and instructors and researchers engaged in the teaching and research of design by experiment. D. G. Kabe retired as Professor of Statistics from St. Mary's University in Canada, having taught statistics and guided Ph.D. students there. Earlier he has been a faculty member at the Dalhousie University, Northern Michigan University, and Wayne State University. He is the author/co-author of more than two hundred research papers and two books. His research interests include design and analysis of experiments, and multivariate statistical analysis. Arjun K. Gupta is Distinguished University Professor and Professor of Mathematics and Statistics at Bowling Green State University, Bowling Green, Ohio. He has written more than 35 invited conferences, symposia, and journal papers and given more than 100 talks at national and international meetings during his 30-plus-year career. He is the co-author or co-editor of 12 books and has written more than 300 research articles. His main areas of interest include multivariate statistical analysis, distribution theory, and change point analysis. He is a Fellow of the American Statistical Association, the Institute of Statisticians, the Royal Statistical Society of England, and the Ohio Academy of Science, and an elected member of the International Statistical Institute HTTP:URL=https://doi.org/10.1007/978-0-387-33893-4

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