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Exploring Data Tables, Trends, and Shapes
von David C. Hoaglin, Frederick Mosteller, John W. Tukey
Verlag: Wiley-IEEE Press
Reihe: Wiley Series in Probability and Statistics Nr. 2
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Kopierschutz: Adobe DRM


Speicherplatz: 20 MB
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ISBN: 978-1-118-15069-6
Auflage: 1. Auflage
Erschienen am 28.09.2011
Sprache: Englisch
Umfang: 576 Seiten

Preis: 125,99 €

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Klappentext

WILEY-INTERSCIENCE PAPERBACK SERIES
The Wiley-Interscience Paperback Series consists ofselected books that have been made more accessible to consumers inan effort to increase global appeal and general circulation. Withthese new unabridged softcover volumes, Wiley hopes to extend thelives of these works by making them available to future generationsof statisticians, mathematicians, and scientists.
"Exploring Data Tables, Trends, and Shapes (EDTTS) waswritten as a companion volume to the same editors' book,Understanding Robust and Exploratory Data Analysis (UREDA). WhereasUREDA is a collection of exploratory and resistant methods ofestimation and display, EDTTS goes a step further, describingmultivariate and more complicated techniques . . . I feel that theauthors have made a very significant contribution in the area ofmultivariate nonparametric methods. This book [is] a valuablesource of reference to researchers in the area."
--Technometrics
"This edited volume . . . provides an important theoretical andphilosophical extension to the currently popular statistical areaof Exploratory Data Analysis, which seeks to reveal structure, orsimple descriptions, in data . . . It is . . . an importantreference volume which any statistical library should considerseriously."
--The Statistician
This newly available and affordably priced paperback version ofExploring Data Tables, Trends, and Shapes presents majoradvances in exploratory data analysis and robust regression methodsand explains the techniques, relating them to classical methods.The book addresses the role of exploratory and robust techniques inthe overall data-analytic enterprise, and it also presents newmethods such as fitting by organized comparisons using the squarecombining table and identifying extreme cells in a sizablecontingency table with probabilistic and exploratory approaches.The book features a chapter on using robust regression in lesstechnical language than available elsewhere. Conceptual support foreach technique is also provided.


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