Nonparametric Hypothesis Testing: Rank and Permutation Methods with Applications in R
β Scribed by Stefano Bonnini, Livio Corain, Marco Marozzi, Luigi Salmaso
- Publisher
- Wiley
- Year
- 2014
- Tongue
- English
- Leaves
- 254
- Series
- Wiley Series in Probability and Statistics
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
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.
β¦ Subjects
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π SIMILAR VOLUMES
Hypotheses Testing for Two Samples Sign Test for Location Parameter for Matched Paired Samples Wilcoxon Signed-Rank Test for Location Parameter for Matched Paired Samples Wilcoxon Rank-Sum Test for Location Parameter for Two Independent Samples Ansari-Bradley Test for Scale Parameter for Two Indep
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real world or who will be participating in the training of real-world statisticians and biostatisticians. In previous editions of this text, my rhetoric
<p>This book offers a new, fairly efficient, and robust alternative to analyzing multivariate data. The analysis of data based on multivariate spatial signs and ranks proceeds very much as does a traditional multivariate analysis relying on the assumption of multivariate normality; the regular L2 no