Permutation Statistical Methods, Softcover reprint of the original 1st ed. 2016 An Integrated Approach

This research monograph provides a synthesis of a number of statistical tests and measures, which, at first consideration, appear disjoint and unrelated. Numerous comparisons of permutation and classical statistical methods are presented, and the two methods are compared via probability values and, where appropriate, measures of effect size.

Permutation statistical methods, compared to classical statistical methods, do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This text takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field in statistics. This topic is new in that it took modern computing power to make permutation methods available to people working in the mainstream of research.

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Preface.- 1.Introduction.- 2.Completely Randomized Data.- 3.Randomized Designs: Interval Data.- 4.Regression Analysis of Interval Data.- 5.Randomized Designs: Ordinal Data, I.- 6.Randomized Designs: Ordinal Data, II.- 7.Randomized Designs: Nominal Data.- 8.Randomized Designs: Nominal Data.- 9.Randomized Block Designs: Interval Data.- 10.Randomized Block Designs: Ordinal Data.- 11.Randomized Block Designs: Nominal Data.- Epilogue.- References.- Author Index.- Subject Index.

Presents a methodological umbrella under which (1) disparate statistical methods are synthesized and integrated and (2) a number of new permutation statistical methods are developed Synthesizes and integrates a large number of existing classical statistics under a common mathematical function Provides computing algorithms for calculating permutation tests, and details the history of permutation statistical methods