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Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science) [Kindle Edition]

Rand R. Wilcox

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Kindle Edition EUR 53,26  
Gebundene Ausgabe EUR 76,08  
Taschenbuch EUR 116,74  
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Produktbeschreibungen

Pressestimmen

..".greatly enhanced...almost twice as large as the first edition. This would now seem to be a good book for everyone to have in their library."
-TECHNOMETRICS, VOL. 47, 2005
..".an outstanding introduction to robust statistics, outlier detection and the bootstrap. There is, to my knowledge, no comparable book written at this level of accessibility." David Leblang, University of Colorado at Boulder.
"It is rather unique, this book. The message that the author aims to deliver is an important one. Most other textbooks aim to illustrate the standard story, using innovative illustrations or clearer exposition. So there is a lot of redundancy out there in statistics books. This book stands out as providing something new and clearly important." Sheila Kennison, Oklahoma State University

Kurzbeschreibung

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 in different situations.

Introduction to Robust Estimation and Hypothesis Testing, Second Edition, focuses on the practical applications of modern, robust methods which can greatly enhance our chances of detecting true differences among groups and true associations among variables.



  • Covers latest developments in robust regression
  • Covers latest improvements in ANOVA
  • Includes newest rank-based methods
  • Describes and illustrated easy to use software

Produktinformation

  • Format: Kindle Edition
  • Dateigröße: 8046 KB
  • Seitenzahl der Print-Ausgabe: 713 Seiten
  • ISBN-Quelle für Seitenzahl: 0123869838
  • Verlag: Academic Press; Auflage: 3 (14. Dezember 2011)
  • Verkauf durch: Amazon Media EU S.à r.l.
  • Sprache: Englisch
  • ASIN: B007N1KRG6
  • Text-to-Speech (Vorlesemodus): Aktiviert
  • X-Ray:
  • Word Wise: Nicht aktiviert
  • Verbesserter Schriftsatz: Nicht aktiviert
  • Amazon Bestseller-Rang: #617.862 Bezahlt in Kindle-Shop (Siehe Top 100 Bezahlt in Kindle-Shop)

  •  Ist der Verkauf dieses Produkts für Sie nicht akzeptabel?

Kundenrezensionen

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Amazon.com: 4.4 von 5 Sternen  5 Rezensionen
4 von 4 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen excellent book 24. Januar 2014
Von jirgarci - Veröffentlicht auf Amazon.com
Format:Kindle Edition|Verifizierter Kauf
Incredibly useful guide to modern statistics using R for a wide audience. Highly recommended for those with a basic understanding of statistics yet annoyed by non-normal data sets. The book presents an good mathematical rationale for all the methods introduced without complex proofs and definitions. Definitely one of the best text in robust statistics. The clear description of the R codes make this book an extraordinary tool for people dealing with the analysis of real world data sets. Still the book could be enriched with more examples.
2 von 2 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen I have used the methods frequently during the last two years and they have really helped me with noisy and bad data sets 1. März 2015
Von Tuomas Vallius - Veröffentlicht auf Amazon.com
Format:Kindle Edition|Verifizierter Kauf
I have the previous Wilcox' book on the same topic. However, this one is more thorough and up to date. I have used the methods frequently during the last two years and they have really helped me with noisy and bad data sets, especially in the presence on non-normality.

An excellent book and well organized material.
3 von 4 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Like the book, don't like the price 20. Mai 2012
Von Dimitri Shvorob - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe
I am not expert on robust statistics, and have not seen other books on the subject - with the price as steep as it is, a serious comparison of alternatives is a must - but will hopefully add value by pointing out that the other two reviews refer to an early, and very different, edition.

If that one had 296 pages, and the current one has 690, you will agree that the book has changed a lot, and the reviews from 2000 may not be very relevant. (The S-PLUS-related comments in particular are completely out of date; third edition is 100% R). It is sad that there have not been more recent reviews to set the record straight - again, I suspect that the almost-$100 price tag is to blame, and hope that Academic Press and the author reconsider this unwise pricing strategy, which has undermined what is really a very worthwhile book.

I have first come across Rand Wilcox's writing in his "Applying contemporary statistical techniques" - if anyone is teaching undergraduate statistics, be sure to take a look - and have found "Introduction to robust estimation and hypothesis testing" to have the same high quality and accessibility. With 700 pages, it covers a lot of ground, isn't "soft" yet does not bog down in mathematical detail, nor does it descend into can't-see-the-forest-for-the-trees slog through a catalog of estimators.

A seriously big collection of R functions implementing the various methods is a seriously big plus - sadly, the author has not found time to provide adequate "help" for his files outside of the book; it is thus not a proper R package (hence, it's downloaded from R-Forge, not from CRAN; you do need to update R to be able to install it via "install.packages", and you do not want to load the source file, as this will take 20 minutes, every time) - but the book is valuable without regard for its R content. Do give it a chance.
1 von 1 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Great book other than the typesetting 17. März 2015
Von JoeT - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
Excellent book on non-parametric analysis.
My only gripe is the publisher. Whoever decided to use the same font for text as they did for the R code, I suppose, never saw any computer book published in this century. Great otherwise.
0 von 3 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen introduction to robust estimation is a good one 3. März 2013
Von EKELE ALIH - Veröffentlicht auf Amazon.com
Format:Gebundene Ausgabe|Verifizierter Kauf
I love the book but the Author should improve in the area of robust regression by being practical in some algorithms so that people can understand and research into the area
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