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Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science)

Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science)

Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling
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Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science) Hardback - 2016

by Wilcox, Rand R

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Academic Press. Used - Good. Ships from UK in 48 hours or less (usually same day). Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. 100% money back guarantee. We are a world class secondhand bookstore based in Hertfordshire, United Kingdom and specialize in high quality textbooks across an enormous variety of subjects. We aim to provide a vast range of textbooks, rare and collectible books at a great price. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. We provide a 100% money back guarantee and are dedicated to providing our customers with the highest standards of service in the bookselling industry.
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Phatpocket Limited is a world class secondhand bookstore located in the Hertfordshire countryside in the United Kingdom. We specialize in textbooks across an enormous variety of subjects. We aim to provide a low cost source of high quality textbooks to the academic community. We also have a sizable collection of rare and collectible books.

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Reader reviews for Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science)

From the publisher

Introduction to Robust Estimating and Hypothesis Testing, 4th Editon, is a 'how-to' on the application of robust methods using available software. Modern robust methods provide improved techniques for dealing with outliers, skewed distribution curvature and heteroscedasticity that can provide substantial gains in power as well as a deeper, more accurate and more nuanced understanding of data. Since the last edition, there have been numerous advances and improvements. They include new techniques for comparing groups and measuring effect size as well as new methods for comparing quantiles. Many new regression methods have been added that include both parametric and nonparametric techniques. The methods related to ANCOVA have been expanded considerably. New perspectives related to discrete distributions with a relatively small sample space are described as well as new results relevant to the shift function. The practical importance of these methods is illustrated using data from real world studies. The R package written for this book now contains over 1200 functions.

New to this edition

  • 35% revised content
  • Covers many new and improved R functions
  • New techniques that deal with a wide range of situations
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