Springer, 2019. - 487 p. - ISBN: 3030209326.
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.
A Brief History of Permutation Methods.
Permutation Statistical Methods.
Central Tendency and Variability.
One-Sample Tests.
Two-Sample Tests.
Matched-Pairs Tests.
Completely-Randomized Designs.
Randomized-Blocks Designs.
Correlation and Regression.
Contingency Tables.
Epilogue.
Author Index.
Subject Index.
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