A Primer of Permutation Statistical Methods

by Kenneth J. Berry, Janis E. Johnston, and Paul W. Mielke, Jr.

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The primary purpose of this textbook is to introduce the reader to a wide variety of elementary permutation statistical methods. Permutation methods are optimal for small data sets and non-random samples, and are free of distributional assumptions. The book follows the conventional structure of most introductory books on statistical methods, and features chapters on central tendency and variability, one-sample tests, two-sample tests, matched-pairs tests, one-way fully-randomized analysis of variance, one-way randomized-blocks analysis of variance, simple regression and correlation, and the analysis of contingency tables. In addition, it introduces and describes a comparatively new permutation-based, chance-corrected measure of effect size.

Because permutation tests and measures are distribution-free, do not assume normality, and do not rely on squared deviations among sample values, they are currently being applied in a wide variety of disciplines. This book presents permutation alternatives to existing classical statistics, and is intended as a textbook for undergraduate statistics courses or graduate courses in the natural, social, and physical sciences, while assuming only an elementary grasp of statistics.


  • ISBN13 9783030209353
  • Publish Date 13 August 2020 (first published 13 August 2019)
  • Publish Status Active
  • Publish Country CH
  • Imprint Springer Nature Switzerland AG
  • Edition 1st ed. 2019
  • Format Paperback
  • Pages 476
  • Language English