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This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.
The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
This book provides a relatively non-technical guide to modern methods. The focus is on applying modern methods using R, understanding when and why classic methods can be unsatisfactory, and fostering a conceptual understanding of the relative merits of different techniques. A recurring theme is that no single method reveals everything one would like to know about the population under study. An appeal of robust methods is that under general conditions they provide much higher power than conventional techniques. Perhaps more importantly, they help provide a deeper and more nuanced understanding of data.
The book is for readers who had at least one semester of statistics, aimed at non-statisticians.
Rand R. Wilcox is Professor of Psychology, USC Dornsife College of Letters, Arts and Sciences. He has written 15 other statistics books, including Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy, 2nd edition (2010), over 400 journal articles, is a former associate editor for 5 statistics journals, is an elected member of the International Statistical Institute and he created the R package, WRS.
Examines properties of robust estimators and their relative merits
Focuses on heteroscedastic techniques, including recent advances dealing multicollinearity
Contains recent advances dealing with measures effect size and outliers, including bad leverage points
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Seiten: | 344 |
| Inhalt: |
xvii
326 S. 57 s/w Illustr. 326 p. 57 illus. |
| ISBN-13: | 9783031417122 |
| ISBN-10: | 3031417127 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: | Wilcox, Rand R. |
| Auflage: | 1st ed. 2023 |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing |
| Maße: | 241 x 160 x 25 mm |
| Von/Mit: | Rand R. Wilcox |
| Erscheinungsdatum: | 26.10.2023 |
| Gewicht: | 0,682 kg |
Rand R. Wilcox is Professor of Psychology, USC Dornsife College of Letters, Arts and Sciences. He has written 15 other statistics books, including Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy, 2nd edition (2010), over 400 journal articles, is a former associate editor for 5 statistics journals, is an elected member of the International Statistical Institute and he created the R package, WRS.
Examines properties of robust estimators and their relative merits
Focuses on heteroscedastic techniques, including recent advances dealing multicollinearity
Contains recent advances dealing with measures effect size and outliers, including bad leverage points
| Erscheinungsjahr: | 2023 |
|---|---|
| Fachbereich: | Wahrscheinlichkeitstheorie |
| Genre: | Mathematik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Buch |
| Seiten: | 344 |
| Inhalt: |
xvii
326 S. 57 s/w Illustr. 326 p. 57 illus. |
| ISBN-13: | 9783031417122 |
| ISBN-10: | 3031417127 |
| Sprache: | Englisch |
| Ausstattung / Beilage: | HC runder Rücken kaschiert |
| Einband: | Gebunden |
| Autor: | Wilcox, Rand R. |
| Auflage: | 1st ed. 2023 |
| Hersteller: |
Springer Nature Switzerland
Springer International Publishing |
| Maße: | 241 x 160 x 25 mm |
| Von/Mit: | Rand R. Wilcox |
| Erscheinungsdatum: | 26.10.2023 |
| Gewicht: | 0,682 kg |
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