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![]( "Buchcover ISBN 9781118763476")
„The book combines an up to date overview with usefulpractical guidance to applications in R, and will be a valuableresource for practitioners and researchers working in a wide rangeof scientific fields including engineering, biostatistics, psychology and medicine.“ (Zentralblatt MATH, 1October 2014)
Nonparametric Hypothesis Testing
Rank and Permutation Methods with Applications in R
von Stefano Bonnini, Livio Corain, Marco Marozzi und Luigi SalmasoA novel presentation of rank and permutation tests, with accessible guidance to applications in R
Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. This book summarizes traditional rank techniques and more recent developments in permutation testing as robust tools for dealing with complex data with low sample size.
Key Features:
* Examines the most widely used methodologies of nonparametric testing.
* Includes extensive software codes in R featuring worked examples, and uses real case studies from both experimental and observational studies.
* Presents and discusses solutions to the most important and frequently encountered real problems in different fields.
Features a supporting website (www. wiley. com/go/hypothesis_testing) containing all of the data sets examined in the book along with ready to use R software codes.
Nonparametric Hypothesis Testing combines an up to date overview with useful practical guidance to applications in R, and will be a valuable resource for practitioners and researchers working in a wide range of scientific fields including engineering, biostatistics, psychology and medicine.
Nonparametric testing problems are frequently encountered in many scientific disciplines, such as engineering, medicine and the social sciences. This book summarizes traditional rank techniques and more recent developments in permutation testing as robust tools for dealing with complex data with low sample size.
Key Features:
* Examines the most widely used methodologies of nonparametric testing.
* Includes extensive software codes in R featuring worked examples, and uses real case studies from both experimental and observational studies.
* Presents and discusses solutions to the most important and frequently encountered real problems in different fields.
Features a supporting website (www. wiley. com/go/hypothesis_testing) containing all of the data sets examined in the book along with ready to use R software codes.
Nonparametric Hypothesis Testing combines an up to date overview with useful practical guidance to applications in R, and will be a valuable resource for practitioners and researchers working in a wide range of scientific fields including engineering, biostatistics, psychology and medicine.
