Nonparametric Hypothesis Testing: Rank and Permutation Methods With Applications in R - Rilegato

Libro 267 di 352: Wiley Series in Probability and Statistics

Bonnini, Stefano; Corain, Livio; Marozzi, Marco; Salmaso, Luigi

 
9781119952374: Nonparametric Hypothesis Testing: Rank and Permutation Methods With Applications in R
Rilegato
ISBN 10: 1119952379 ISBN 13: 9781119952374
Casa editrice: John Wiley & Sons Inc, 2014

Sinossi

A 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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Informazioni sull'autore

Stefano Bonnini, Assistant Professor of Statistics, Faculty of Economics, Department of Economics, University of Ferrara, Italy.

Livio Corain, Assistant Professor of Statistics, Faculty of Engineering, Department of Management and Engineering, University of Padova, Italy.

Marco Marozzi, Associate Professor of Statistics, Faculty of Economics, Department of Economics and Statistics, University of Calabria, Italy.

Luigi Salmaso, Full Professor of Statistics, Faculty of Engineering, University of Padova, Italy.

Dalla quarta di copertina

A 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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
John Wiley & Sons Inc
Data di pubblicazione
2014
Lingua
Inglese
ISBN 10 
1119952379
ISBN 13 
9781119952374
Rilegatura
Copertina rigida
Numero di pagine
220
Contatto del produttore
non disponibile
Persona responsabile
non disponibile