Format:
Online-Ressource (XIX, 517 p. 51 illus, online resource)
ISBN:
9783319027449
Series Statement:
SpringerLink
Content:
Preface -- 1.Introduction -- 2.1920-1939 -- 3.1940-1959 -- 4.1960-1979 -- 5.1980-2000 -- 6.Beyond 2000 -- Epilogue -- References -- Acronyms -- Name Index -- Subject Index
Content:
The focus of this book is on the birth and historical development of permutation statistical methods from the early 1920s to the near present. Beginning with the seminal contributions of R.A. Fisher, E.J.G. Pitman, and others in the 1920s and 1930s, permutation statistical methods were initially introduced to validate the assumptions of classical statistical methods. Permutation methods have advantages over classical methods in that they are optimal for small data sets and non-random samples, are data-dependent, and are free of distributional assumptions. Permutation probability values may be exact, or estimated via moment- or resampling-approximation procedures. Because permutation methods are inherently computationally-intensive, the evolution of computers and computing technology that made modern permutation methods possible accompanies the historical narrative. Permutation analogs of many well-known statistical tests are presented in a historical context, including multiple correlation and regression, analysis of variance, contingency table analysis, and measures of association and agreement. A non-mathematical approach makes the text accessible to readers of all levels
Note:
Description based upon print version of record
,
Preface; Acronyms; Contents; 1 Introduction; 1.1 Overview of This Chapter; 1.2 Two Models of Statistical Inference; 1.3 Permutation Tests; 1.3.1 Exact Permutation Tests; 1.3.2 Moment-Approximation Permutation Tests; 1.3.3 Resampling-Approximation Permutation Tests; 1.3.4 Compared with Parametric Tests; 1.3.5 The Bootstrap and the Jackknife; 1.4 Student's t Test; 1.4.1 An Exact Permutation t Test; 1.4.2 A Moment-Approximation t Test; 1.4.3 A Resampling-Approximation t Test; 1.5 An Example Data Analysis; 1.6 Overviews of Chaps. 2-6; Chapter 2: 1920-1939; Chapter 3: 1940-1959
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Chapter 4: 1960-1979Chapter 5: 1980-2000; Chapter 6: Beyond 2000; Epilogue; 2 1920-1939; 2.1 Overview of This Chapter; 2.2 Neyman-Fisher-Geary and the Beginning; 2.2.1 Spława-Neyman and Agricultural Experiments; 2.2.2 Fisher and the Binomial Distribution; 2.2.3 Geary and Correlation; 2.3 Fisher and the Variance-Ratio Statistic; 2.3.1 Snedecor and the F Distribution; 2.4 Eden-Yates and Non-normal Data; 2.5 Fisher and 2 2 Contingency Tables; 2.6 Yates and the Chi-Squared Test for Small Samples; 2.6.1 Calculation with an Arbitrary Initial Value; 2.7 Irwin and Fourfold Contingency Tables
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2.8 The Rothamsted Manorial Estate2.8.1 The Rothamsted Lady Tasting Tea Experiment; 2.8.2 Analysis of The Lady Tasting Tea Experiment; 2.9 Fisher and the Analysis of Darwin's Zea mays Data; 2.10 Fisher and the Coefficient of Racial Likeness; 2.11 Hotelling-Pabst and Simple Bivariate Correlation; 2.12 Friedman and Analysis of Variance for Ranks; 2.13 Welch's Randomized Blocks and Latin Squares; 2.14 Egon Pearson on Randomization; 2.15 Pitman and Three Seminal Articles; 2.15.1 Permutation Analysis of Two Samples; 2.15.2 Permutation Analysis of Correlation
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2.15.3 Permutation Analysis of Variance2.16 Welch and the Correlation Ratio; 2.17 Olds and Rank-Order Correlation; 2.18 Kendall and Rank Correlation; 2.19 McCarthy and Randomized Blocks; 2.20 Computing and Calculators; 2.20.1 The Method of Differences; 2.20.2 Statistical Computing in the 1920s and 1930s; 2.21 Looking Ahead; 3 1940-1959; 3.1 Overview of This Chapter; 3.2 Development of Computing; 3.3 Kendall-Babington Smith and Paired Comparisons; 3.4 Dixon and a Two-Sample Rank Test; 3.5 Swed-Eisenhart and Tables for the Runs Test; 3.6 Scheffé and Non-parametric Statistical Inference
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3.7 Wald-Wolfowitz and Serial Correlation3.8 Mann and a Test of Randomness Against Trend; 3.9 Barnard and 2 2 Contingency Tables; 3.10 Wilcoxon and the Two-Sample Rank-Sum Test; 3.10.1 Unpaired Samples; 3.10.2 Paired Samples; 3.11 Festinger and the Two-Sample Rank-Sum Test; 3.12 Mann-Whitney and a Two-Sample Rank-Sum Test; 3.13 Whitfield and a Measure of Ranked Correlation; 3.13.1 An Example of Whitfield's Approach; 3.14 Olmstead-Tukey and the Quadrant-Sum Test; 3.15 Haldane-Smith and a Test for Birth-Order Effects; 3.16 Finney and the Fisher-Yates Test for 2 2 Tables
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3.17 Lehmann-Stein and Non-parametric Tests
Additional Edition:
ISBN 9783319027432
Additional Edition:
Erscheint auch als Druck-Ausgabe Berry, Kenneth J. A Chronicle of permutation statistical methods Cham : Springer, 2014 ISBN 9783319027432
Language:
English
Subjects:
Mathematics
Keywords:
Statistik
;
Geschichte 1920-2000
DOI:
10.1007/978-3-319-02744-9
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