An introduction to nonparametric statistics:
An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques incl...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press
2021
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| Ausgabe: | First edition |
| Schriftenreihe: | Texts in statistical science series
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| Schlagworte: | |
| Zusammenfassung: | An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention is paid to the intellectual development of the field, with a thorough review of bibliographical references. Computational tools, in R and SAS, are developed and illustrated via examples. Exercises designed to reinforce examples are included.This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology, elementary probability, and regression. Mathematical prerequisites include calculus through multivariate differentiation and integration, and, ideally, a course in matrix algebra. |
| Beschreibung: | XII, 212 Seiten Illustrationen, Diagramme |
| ISBN: | 9780367194840 |
Internformat
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| 520 | 3 | |a An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention is paid to the intellectual development of the field, with a thorough review of bibliographical references. Computational tools, in R and SAS, are developed and illustrated via examples. Exercises designed to reinforce examples are included.This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology, elementary probability, and regression. Mathematical prerequisites include calculus through multivariate differentiation and integration, and, ideally, a course in matrix algebra. | |
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Datensatz im Suchindex
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| author | Kolassa, John E. 1963- |
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| author_facet | Kolassa, John E. 1963- |
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| author_sort | Kolassa, John E. 1963- |
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| bvnumber | BV048883921 |
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| contents | Features Rank-based techniques including sign, Kruskal-Wallis, Friedman, Mann-Whitney and Wilcoxon tests are presented Tests are inverted to produce estimates and confidence intervals Multivariate tests are explored Techniques reflecting the dependence of a response variable on explanatory variables are presented Density estimation is explored The bootstrap and jackknife are discussed |
| ctrlnum | (OCoLC)1374561946 (DE-599)BVBBV048883921 |
| dewey-full | 519.5 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5 |
| dewey-search | 519.5 |
| dewey-sort | 3519.5 |
| dewey-tens | 510 - Mathematics |
| discipline | Psychologie Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Psychologie Mathematik Wirtschaftswissenschaften |
| edition | First edition |
| format | Book |
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| id | DE-604.BV048883921 |
| illustrated | Illustrated |
| index_date | 2024-07-03T21:46:55Z |
| indexdate | 2024-07-10T09:48:46Z |
| institution | BVB |
| isbn | 9780367194840 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-034148589 |
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| physical | XII, 212 Seiten Illustrationen, Diagramme |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | CRC Press |
| record_format | marc |
| series2 | Texts in statistical science series |
| spelling | Kolassa, John E. 1963- Verfasser (DE-588)106849459X aut An introduction to nonparametric statistics John A. Kolassa First edition Boca Raton ; London ; New York CRC Press 2021 XII, 212 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Texts in statistical science series Features Rank-based techniques including sign, Kruskal-Wallis, Friedman, Mann-Whitney and Wilcoxon tests are presented Tests are inverted to produce estimates and confidence intervals Multivariate tests are explored Techniques reflecting the dependence of a response variable on explanatory variables are presented Density estimation is explored The bootstrap and jackknife are discussed An Introduction to Nonparametric Statistics presents techniques for statistical analysis in the absence of strong assumptions about the distributions generating the data. Rank-based and resampling techniques are heavily represented, but robust techniques are considered as well. These techniques include one-sample testing and estimation, multi-sample testing and estimation, and regression. Attention is paid to the intellectual development of the field, with a thorough review of bibliographical references. Computational tools, in R and SAS, are developed and illustrated via examples. Exercises designed to reinforce examples are included.This text is intended for a graduate student in applied statistics. The course is best taken after an introductory course in statistical methodology, elementary probability, and regression. Mathematical prerequisites include calculus through multivariate differentiation and integration, and, ideally, a course in matrix algebra. Regression (DE-588)1168830583 gnd rswk-swf Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd rswk-swf Programmiersprache (DE-588)4047409-4 gnd rswk-swf Nichtparametrische Statistik (DE-588)4226777-8 gnd rswk-swf Methode (DE-588)4038971-6 gnd rswk-swf Angewandte Statistik Statistische Methodik Mathematische Voraussetzungen Nichtparametrische Statistik (DE-588)4226777-8 s Programmiersprache (DE-588)4047409-4 s Methode (DE-588)4038971-6 s Wahrscheinlichkeitstheorie (DE-588)4079013-7 s Regression (DE-588)1168830583 u DE-604 |
| spellingShingle | Kolassa, John E. 1963- An introduction to nonparametric statistics Features Rank-based techniques including sign, Kruskal-Wallis, Friedman, Mann-Whitney and Wilcoxon tests are presented Tests are inverted to produce estimates and confidence intervals Multivariate tests are explored Techniques reflecting the dependence of a response variable on explanatory variables are presented Density estimation is explored The bootstrap and jackknife are discussed Regression (DE-588)1168830583 gnd Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd Programmiersprache (DE-588)4047409-4 gnd Nichtparametrische Statistik (DE-588)4226777-8 gnd Methode (DE-588)4038971-6 gnd |
| subject_GND | (DE-588)1168830583 (DE-588)4079013-7 (DE-588)4047409-4 (DE-588)4226777-8 (DE-588)4038971-6 |
| title | An introduction to nonparametric statistics |
| title_auth | An introduction to nonparametric statistics |
| title_exact_search | An introduction to nonparametric statistics |
| title_exact_search_txtP | An introduction to nonparametric statistics |
| title_full | An introduction to nonparametric statistics John A. Kolassa |
| title_fullStr | An introduction to nonparametric statistics John A. Kolassa |
| title_full_unstemmed | An introduction to nonparametric statistics John A. Kolassa |
| title_short | An introduction to nonparametric statistics |
| title_sort | an introduction to nonparametric statistics |
| topic | Regression (DE-588)1168830583 gnd Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd Programmiersprache (DE-588)4047409-4 gnd Nichtparametrische Statistik (DE-588)4226777-8 gnd Methode (DE-588)4038971-6 gnd |
| topic_facet | Regression Wahrscheinlichkeitstheorie Programmiersprache Nichtparametrische Statistik Methode |
| work_keys_str_mv | AT kolassajohne anintroductiontononparametricstatistics |