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Introduction to Robust Estimation and Hypothesis Testing de Rand R. Wilcox

Introduction to Robust Estimation and Hypothesis Testing

Autor Rand R. Wilcox
en Limba Engleză Paperback – 15 feb 2022
Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful ‘how-to’ on the application of robust methods utilizing easy-to-use software. This trusted resource provides an overview of modern robust methods, including improved techniques for dealing with outliers, skewed distribution curvature, and heteroscedasticity that can provide substantial gains in power. Coverage includes techniques for comparing groups and measuring effect size, current methods for comparing quantiles, and expanded regression methods for both parametric and nonparametric techniques. The practical importance of these varied methods is illustrated using data from real world studies. Over 1700 R functions are included to support comprehension and practice.

  • Includes the latest developments in robust regression
  • Provides many new, improved and accessible R functions
  • Offers comprehensive coverage of ANOVA and ANCOVA methods
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Specificații

ISBN-13: 9780128200988
ISBN-10: 0128200987
Pagini: 928
Ilustrații: 120 illustrations (20 in full color)
Dimensiuni: 191 x 235 x 36 mm
Greutate: 1.48 kg
Ediția:5
Editura: ELSEVIER SCIENCE

Public țintă

Advanced UG / graduate students in mathematics and applied courses
Researchers/Professionals
Robust Statistics, Robust Methods in Statistics

Cuprins

1. Introduction 2. A Foundation for Robust Methods 3. Estimating Measures of Location and Scale 4. Confidence Intervals in the One-Sample Case 5. Comparing Two Groups 6. Some Multivariate Methods 7. One-Way and Higher Designs for Independent Groups 8. Comparing Multiple Dependent Groups 9. Correlation and Tests of Independence 10. Robust Regression 11. More Regression Methods 12. ANCOVA

Descriere

Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition is a useful ‘how-to’ on the application of robust methods utilizing easy-to-use software. This trusted resource provides an overview of modern robust methods, including improved techniques for dealing with outliers, skewed distribution curvature, and heteroscedasticity that can provide substantial gains in power. Coverage includes techniques for comparing groups and measuring effect size, current methods for comparing quantiles, and expanded regression methods for both parametric and nonparametric techniques. The practical importance of these varied methods is illustrated using data from real world studies. Over 1700 R functions are included to support comprehension and practice.

 

 

  • Includes the latest developments in robust regression
  • Provides many new, improved and accessible R functions
  • Offers comprehensive coverage of ANOVA and ANCOVA methods