Overview

Provides a self-contained comprehensive treatment of both one-sample and K-sample goodness-of-fit methods by linking them to a common theory backbone

Contains many data examples, including R-code and a specific R-package for comparing distributions

Emphesises informative statistical analysis rather than plain statistical hypothesis testing

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9780387928845

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Reviews

<p>From the reviews: <p> Comparing distributions means mainly goodness-of-fit testing. A lot of details are cited from the huge reference list, which I like very much. At the end of the sections some practical guidelines are given which are very helpful. The monograph is of interest for applied statisticians as well as for research mathematicians. It contains a good overview of tests and methods. It can be recommended for advanced seminars on testing. I can warmly recommend it. (Arnold Janssen, Mathematical Reviews, Issue 2010 k)<p> This outstanding book is about goodness of fit (GOF) testing . In addition the book presents some graphical tools for comparing distributions with its focus on graphs that are closely related to statistical tests. The book contains some theory with numerous examples that are useful for both applied statisticians and nonstatistician practitioners. In conclusion this book provides considerable information for a wide range of Technometrics readers and it is a

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