Introduction to Robust Estimation and Hypothesis Testing

Produk Detail:
  • Author : Rand R. Wilcox
  • Publisher : Academic Press
  • Pages : 928 pages
  • ISBN : 0128200995
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Introduction to Robust Estimation and Hypothesis Testing

Download or Read online Introduction to Robust Estimation and Hypothesis Testing full in PDF, ePub and kindle. this book written by Rand R. Wilcox and published by Academic Press which was released on 18 September 2021 with total page 928 pages. We cannot guarantee that Introduction to Robust Estimation and Hypothesis Testing book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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

Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimation and Hypothesis Testing
  • Author : Rand R. Wilcox
  • Publisher : Academic Press
  • Release : 18 September 2021
GET THIS BOOK Introduction to Robust Estimation and Hypothesis Testing

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

Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimation and Hypothesis Testing
  • Author : Rand R. Wilcox
  • Publisher : Academic Press
  • Release : 05 January 2005
GET THIS BOOK Introduction to Robust Estimation and Hypothesis Testing

This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform

Introduction to Robust Estimation and Hypothesis Testing 3rd Edition

Introduction to Robust Estimation and Hypothesis Testing  3rd Edition
  • Author : Rand Wilcox
  • Publisher : Unknown
  • Release : 06 July 2022
GET THIS BOOK Introduction to Robust Estimation and Hypothesis Testing 3rd Edition

This revised book provides a thorough explanation of the foundation of robust methods, incorporating the latest updates on R and S-Plus, robust ANOVA (Analysis of Variance) and regression. It guides advanced students and other professionals through the basic strategies used for developing practical solutions to problems, and provides a brief background on the foundations of modern methods, placing the new methods in historical context. Author Rand Wilcox includes chapter exercises and many real-world examples that illustrate how various methods perform

Robust Estimation and Hypothesis Testing

Robust Estimation and Hypothesis Testing
  • Author : Moti Lal Tiku
  • Publisher : New Age International
  • Release : 01 January 2004
GET THIS BOOK Robust Estimation and Hypothesis Testing

In Statistical Theory And Practice, A Certain Distribution Is Usually Assumed And Then Optimal Solutions Sought. Since Deviations From An Assumed Distribution Are Very Common, One Cannot Feel Comfortable With Assuming A Particular Distribution And Believing It To Be Exactly Correct. That Brings The Robustness Issue In Focus. In This Book, We Have Given Statistical Procedures Which Are Robust To Plausible Deviations From An Assumed Mode. The Method Of Modified Maximum Likelihood Estimation Is Used In Formulating These Procedures. The

Handbook of Parametric and Nonparametric Statistical Procedures

Handbook of Parametric and Nonparametric Statistical Procedures
  • Author : David Sheskin
  • Publisher : Chapman and Hall/CRC
  • Release : 19 January 2007
GET THIS BOOK Handbook of Parametric and Nonparametric Statistical Procedures

With more than 500 pages of new material, the Handbook of Parametric and Nonparametric Statistical Procedures, Fourth Edition carries on the esteemed tradition of the previous editions, providing up-to-date, in-depth coverage of now more than 160 statistical procedures. The book also discusses both theoretical and practical statistical topics, such as experimental design, experimental control, and statistical analysis. Eliminating the need to search across numerous books, this handbook provides you with everything you need to know about parametric and nonparametric statistical procedures. It

Real Data Analysis

Real Data Analysis
  • Author : Shlomo S. Sawilowsky
  • Publisher : Information Age Pub Incorporated
  • Release : 06 July 2022
GET THIS BOOK Real Data Analysis

The invited authors of this edited volume have been prolific in the arena of Real Data Analysis (RDA) as it applies to the social and behavioral sciences, especially in the disciplines of education and psychology. Combined, this brain trust represents 3,247 articles in refereed journals, 127 books published, US $45.3 Million in extramural research funding, 34 teaching and 92 research awards, serve(d) as Editor/Assistant Editor/Editorial Board Member for 95 peer reviewed journals, and provide( d) ad hoc reviews for 362 journals. Their enormous footprint