Chi-Squared Goodness of Fit Tests with Applications


  • N. Balakrishnan, McMaster University, Hamilton, Canada
  • Vassilly Voinov
  • M.S Nikulin

Chi-Squared Goodness of Fit Tests with Applications provides a thorough and complete context for the theoretical basis and implementation of Pearson’s monumental contribution and its wide applicability for chi-squared goodness of fit tests. The book is ideal for researchers and scientists conducting statistical analysis in processing of experimental data as well as to students and practitioners with a good mathematical background who use statistical methods. The historical context, especially Chapter 7, provides great insight into importance of this subject with an authoritative author team.  This reference includes the most recent application developments in using these methods and models.
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Researchers, professionals and specialists in applied mathematical statistics; graduate students and postgraduate students interested in problems of applied mathematical statistics; students and postgraduate students who use methods of statistical analysis in processing of experimental data; -specialists (researchers) who analyze data of experimental investigations (in applications).


Book information

  • Published: January 2013
  • ISBN: 978-0-12-397194-4


"The book covers modifications and advances of chi-squared test in cases of various situations. On the whole, the book has a highly mathematical treatment and will be very useful to the researchers working on problems related to chi-squared tests of statistical hypothesis testing."--Zentralblatt MATH, 1276.62027
"The primary purpose of this book is to provide a detailed exploration of the theory, methods, and applications of the chi-squared goodness of fit test first advanced by Karl Pearson over 100 years ago."--Reference and Research, April 2013

Table of Contents

Chi-Squared Tests and Modifications: Theory and Applications, Introduction: Historical Notes; Some probability models used in the book, Wald’s method and NRR test, Wald’s method and HRM test; Modifications based on UMVUEs; Vector-valued tests; Some Applications of Modified Chi-squared Tests;  Appendices