Introduction to Robust Estimation and Hypothesis Testing

"This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--

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  • Author : Rand R. Wilcox
  • Publisher : Academic Press
  • Pages : 690 pages
  • ISBN : 0123869838
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKIntroduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimation and Hypothesis Testing

Introduction to Robust Estimation and Hypothesis Testing
  • Author : Rand R. Wilcox
  • Publisher : Academic Press
  • Release : 23 May 2022
GET THIS BOOKIntroduction to Robust Estimation and Hypothesis Testing

"This book focuses on the practical aspects of modern and robust statistical methods. The increased accuracy and power of modern methods, versus conventional approaches to the analysis of variance (ANOVA) and regression, is remarkable. Through a combination of theoretical developments, improved and more flexible statistical methods, and the power of the computer, it is now possible to address problems with standard methods that seemed insurmountable only a few years ago"--

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 BOOKIntroduction 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

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

Parameter Estimation and Hypothesis Testing in Linear Models

Parameter Estimation and Hypothesis Testing in Linear Models
  • Author : Karl-Rudolf Koch
  • Publisher : Springer Science & Business Media
  • Release : 09 March 2013
GET THIS BOOKParameter Estimation and Hypothesis Testing in Linear Models

A treatment of estimating unknown parameters, testing hypotheses and estimating confidence intervals in linear models. Readers will find here presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as well as the mixed model for estimating random parameters. A chapter on the robust estimation of parameters and several examples have been added to this second edition. The necessary theorems of vector and matrix algebra and

Introduction to the New Statistics

Introduction to the New Statistics
  • Author : Geoff Cumming,Robert Calin-Jageman
  • Publisher : Routledge
  • Release : 04 October 2016
GET THIS BOOKIntroduction to the New Statistics

This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective

An Introduction to Probability and Statistics

An Introduction to Probability and Statistics
  • Author : Vijay K. Rohatgi,A.K. Md. Ehsanes Saleh
  • Publisher : John Wiley & Sons
  • Release : 06 August 2015
GET THIS BOOKAn Introduction to Probability and Statistics

A well-balanced introduction to probability theory and mathematical statistics Featuring updated material, An Introduction to Probability and Statistics, Third Edition remains a solid overview to probability theory and mathematical statistics. Divided intothree parts, the Third Edition begins by presenting the fundamentals and foundationsof probability. The second part addresses statistical inference, and the remainingchapters focus on special topics. An Introduction to Probability and Statistics, Third Edition includes: A new section on regression analysis to include multiple regression, logistic regression, and Poisson

Introduction to Statistical Machine Learning

Introduction to Statistical Machine Learning
  • Author : Masashi Sugiyama
  • Publisher : Morgan Kaufmann
  • Release : 31 October 2015
GET THIS BOOKIntroduction to Statistical Machine Learning

Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials. Introduction to Statistical Machine Learning provides a general introduction to machine learning that covers a wide range

Introduction to Robust Estimation and Hypothesis Testing, 3rd Edition

Introduction to Robust Estimation and Hypothesis Testing, 3rd Edition
  • Author : Rand Wilcox
  • Publisher : Unknown Publisher
  • Release : 23 May 2022
GET THIS BOOKIntroduction 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

Applied Econometrics with R

Applied Econometrics with R
  • Author : Christian Kleiber,Achim Zeileis
  • Publisher : Springer Science & Business Media
  • Release : 10 December 2008
GET THIS BOOKApplied Econometrics with R

R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and

Linear Models in Statistics

Linear Models in Statistics
  • Author : Alvin C. Rencher,G. Bruce Schaalje
  • Publisher : John Wiley & Sons
  • Release : 18 January 2008
GET THIS BOOKLinear Models in Statistics

The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated

An Adventure in Statistics

An Adventure in Statistics
  • Author : Andy Field
  • Publisher : SAGE
  • Release : 11 May 2016
GET THIS BOOKAn Adventure in Statistics

Shortlisted for the British Psychological Society Book Award 2017 Shortlisted for the British Book Design and Production Awards 2016 Shortlisted for the Association of Learned & Professional Society Publishers Award for Innovation in Publishing 2016 An Adventure in Statistics: The Reality Enigma by best-selling author and award-winning teacher Andy Field offers a better way to learn statistics. It combines rock-solid statistics coverage with compelling visual story-telling to address the conceptual difficulties that students learning statistics for the first time often encounter in introductory courses

Using R for Principles of Econometrics

Using R for Principles of Econometrics
  • Author : Constantin Colonescu
  • Publisher : Lulu.com
  • Release : 05 January 2018
GET THIS BOOKUsing R for Principles of Econometrics

This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.

Introduction to Econometrics

Introduction to Econometrics
  • Author : James H. Stock,Mark W. Watson
  • Publisher : Pearson
  • Release : 06 January 2015
GET THIS BOOKIntroduction to Econometrics

For courses in Introductory Econometrics Engaging applications bring the theory and practice of modern econometrics to life. Ensure students grasp the relevance of econometrics with Introduction to Econometrics–the text that connects modern theory and practice with motivating, engaging applications. The Third Edition Update maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. This program provides a better teaching and learning experience–for you and your students. Here’