Chi-Squared Goodness of Fit Tests with Applications

Nonfiction, Science & Nature, Mathematics, Probability, Statistics
Cover of the book Chi-Squared Goodness of Fit Tests with Applications by N. Balakrishnan, Vassilly Voinov, M.S Nikulin, Elsevier Science
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Author: N. Balakrishnan, Vassilly Voinov, M.S Nikulin ISBN: 9780123977830
Publisher: Elsevier Science Publication: January 25, 2013
Imprint: Academic Press Language: English
Author: N. Balakrishnan, Vassilly Voinov, M.S Nikulin
ISBN: 9780123977830
Publisher: Elsevier Science
Publication: January 25, 2013
Imprint: Academic Press
Language: English

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.

  • Systematic presentation with interesting historical context and coverage of the fundamentals of the subject
  • Presents modern model validity methods, graphical techniques, and computer-intensive methods
  • Recent research and a variety of open problems
  • Interesting real-life examples for practitioners
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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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