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Robust nonparametric statistical methods / Thomas P. Hettmansperger ; Joseph W. McKean.

By: Contributor(s): Material type: TextTextSeries: Chapman & hall/crc monographs on statistics & applied probabilityPublication details: Boca Raton, FL : CRC Press, c2011.Edition: 2nd edDescription: xvii, 535 p. : ill. ; 27 cmISBN:
  • 9781439809082 (hardback)
Subject(s): DDC classification:
  • 519.5 22 HET/R
Other classification:
  • MAT029000
Summary: "Often referred to as distribution-free methods, nonparametric methods do not rely on assumptions that the data are drawn from a given probability distribution. With an emphasis on Wilcoxon rank methods that enable a unified approach to data analysis, this book presents a unique overview of robust nonparametric statistical methods. Drawing on examples from various disciplines, the relevant R code for these examples, as well as numerous exercises for self-study, the text covers location models, regression models, designed experiments, and multivariate methods. This edition features a new chapter on cluster correlated data"-- Provided by publisher.
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Holdings
Item type Current library Home library Call number Status Date due Barcode Item holds
Text Book Text Book Central Library, IIT Bhubaneswar Central Library, IIT Bhubaneswar 519.5 HET/R (Browse shelf(Opens below)) Available TB157
Text Book Text Book Central Library, IIT Bhubaneswar Central Library, IIT Bhubaneswar 519.5 HET/R (Browse shelf(Opens below)) Available TB158
Course Reserve Course Reserve Central Library, IIT Bhubaneswar Central Library, IIT Bhubaneswar 519.5 HET/R (Browse shelf(Opens below)) Not for loan TB159
Total holds: 0

Includes bibliographical references and indexes.

"Often referred to as distribution-free methods, nonparametric methods do not rely on assumptions that the data are drawn from a given probability distribution. With an emphasis on Wilcoxon rank methods that enable a unified approach to data analysis, this book presents a unique overview of robust nonparametric statistical methods. Drawing on examples from various disciplines, the relevant R code for these examples, as well as numerous exercises for self-study, the text covers location models, regression models, designed experiments, and multivariate methods. This edition features a new chapter on cluster correlated data"-- Provided by publisher.

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