A primer of permutation statistical methods:
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...
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Format: | Buch |
Sprache: | English |
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Cham
Springer
[2019]
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Schlagworte: | |
Zusammenfassung: | 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 |
Beschreibung: | 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 Introduction. - 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 |
Beschreibung: | xxxiii, 476 p 759 grams |
ISBN: | 9783030209353 |
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500 | |a 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 | ||
500 | |a Introduction. - 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 | ||
520 | |a 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 | ||
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spelling | Berry, Kenneth J. Verfasser (DE-588)1105489388 aut A primer of permutation statistical methods Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke, Jr. Cham Springer [2019] xxxiii, 476 p 759 grams txt rdacontent n rdamedia nc rdacarrier 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 Introduction. - 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 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 bicssc bisacsh Statistics Biostatistics Combinatorics Mathematics History Statistics Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik Johnston, Janis E. 1957- Verfasser (DE-588)1105494063 aut Mielke, Paul W. Verfasser (DE-588)1105493067 aut Erscheint auch als Online-Ausgabe 978-3-030-20933-9 |
spellingShingle | Berry, Kenneth J. Johnston, Janis E. 1957- Mielke, Paul W. A primer of permutation statistical methods bicssc bisacsh Statistics Biostatistics Combinatorics Mathematics History Statistics |
title | A primer of permutation statistical methods |
title_auth | A primer of permutation statistical methods |
title_exact_search | A primer of permutation statistical methods |
title_exact_search_txtP | A primer of permutation statistical methods |
title_full | A primer of permutation statistical methods Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke, Jr. |
title_fullStr | A primer of permutation statistical methods Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke, Jr. |
title_full_unstemmed | A primer of permutation statistical methods Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke, Jr. |
title_short | A primer of permutation statistical methods |
title_sort | a primer of permutation statistical methods |
topic | bicssc bisacsh Statistics Biostatistics Combinatorics Mathematics History Statistics |
topic_facet | bicssc bisacsh Statistics Biostatistics Combinatorics Mathematics History Statistics |
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