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Titlebook: A Primer of Permutation Statistical Methods; Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke, Textbook 2019 Springer Nature Switzerland

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發(fā)表于 2025-3-21 18:59:47 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱A Primer of Permutation Statistical Methods
影響因子2023Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke,
視頻videohttp://file.papertrans.cn/142/141894/141894.mp4
發(fā)行地址Offers an essential overview of permutation statistical methods.Presents permutation statistical methods as viable alternatives to classical statistics.Illustrated with a range of real-world examples
圖書(shū)封面Titlebook: A Primer of Permutation Statistical Methods;  Kenneth J. Berry,Janis E. Johnston,Paul W. Mielke, Textbook 2019 Springer Nature Switzerland
影響因子.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
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Simulation of Internal Combustion Engines,of variance for ranks, the Bartlett–Nanda–Pillai trace test for multivariate analysis of variance, and a permutation-based alternative for the four conventional measures of effect size for multi-sample tests: Cohen’s ., Pearson’s .., Kelley’s ., and Hays’ ..
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https://doi.org/10.1007/978-0-387-75967-8iedman’s two-way analysis of variance for ranks, and a permutation-based alternative for the four conventional measures of effect size for randomized-blocks designs: Hays’ ., Pearson’s .., Cohen’s partial .., and Cohen’s ...
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https://doi.org/10.1007/978-981-16-2450-6st, the Wilcoxon–Mann–Whitney two-sample rank-sum test, Hotelling’s multivariate .. test for two independent samples, and a permutation-based alternative for the four conventional measures of effect size for two-sample tests: Cohen’s ., Pearson’s .., Kelley’s .., and Hays’ ..
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Textbook 2019are 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-pa
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https://doi.org/10.1007/978-981-16-2450-6e-sample rank-score data, and analysis of one-sample multivariate data. Included in this chapter are permutation versions of Student’s one-sample . test, Wilcoxon’s signed-ranks test, the sign test, and a permutation-based alternative for the two conventional measures of effect size for one-sample tests: Cohen’s . and Pearson’s ...
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Textbook 2019hey 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
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