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A Primer of Permutation Statistical Methods

  • Kenneth J. Berry
  • Janis E. Johnston
  • Paul W. Mielke, Jr.
Textbook

Table of contents

  1. Front Matter
    Pages i-xxiii
  2. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 1-15
  3. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 17-55
  4. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 57-82
  5. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 83-100
  6. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 101-152
  7. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 153-205
  8. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 207-255
  9. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 257-313
  10. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 315-359
  11. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 361-407
  12. Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke Jr.
    Pages 409-459
  13. Back Matter
    Pages 461-476

About this book

Introduction

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.

Keywords

62gxx, 62-07, 62-03, 01-08, 62axx Permutation Exact tests Monte Carlo tests Randomization Moment approximation tests Contingency tables

Authors and affiliations

  • Kenneth J. Berry
    • 1
  • Janis E. Johnston
    • 2
  • Paul W. Mielke, Jr.
    • 3
  1. 1.Department of SociologyColorado State UniversityFort CollinsUSA
  2. 2.AlexandriaVirginiaUSA
  3. 3.Department of StatisticsColorado State UniversityFort CollinsUSA

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