Permutation Statistical Methods

Permutation Statistical Methods: An Integrated Approach
Springer | Statistics | June 04, 2016 | ISBN-10: 3319287680 | 622 pages | pdf | 11.15 mb

Authors: Berry, Kenneth J., Mielke, Jr., Paul W., Johnston, Janis E.
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

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

Number of Illustrations and Tables
180 b/w illustrations
Statistical Theory and Methods
Statistics for Life Sciences, Medicine, Health Sciences
History of Science

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