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OLS Field Name OLS Field Data
Main Title A guide to chi-squared testing /
Author Greenwood, P. E.,
Other Authors
Author Title of a Work
Nikulin, M. S.
Publisher Wiley,
Year Published 1996
OCLC Number 33969906
ISBN 047155779X; 9780471557791
Subjects Chi-square test. ; Chi-kwadraatverdeling. ; Tests d'hypothèses (statistique) ; Khi-carré, Test du.
Internet Access
Description Access URL
Contributor biographical information http://catdir.loc.gov/catdir/bios/wiley041/95052754.html
Publisher description http://catdir.loc.gov/catdir/description/wiley031/95052754.html
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
EJBM  QA277.3.G74 1996 Headquarters Library/Washington,DC 12/04/2018
Collation xii, 280 pages ; 24 cm.
Notes
"A Wiley-Interscience publication." Includes bibliographical references (pages 259-274) and index.
Contents Notes
Ch. 1. The Chi-squared Test of Pearson -- Ch. 2. The Chi-squared Test for a Composite Hypothesis -- Ch. 3. The Chi-squared Test for an Exponential Family of Distributions -- Ch. 4. Some Additional Examples -- Appendix: Multivariate Normal and Chi-squared Distributions: Some Definitions and Basic Properties. Chi-squared testing is one of the most commonly applied statistical techniques. It provides reliable answers for researchers in a wide range of fields, including engineering, manufacturing, finance, agriculture, and medicine. A Guide to Chi-Squared Testing brings readers up to date on recent innovations and important material previously published only in the former Soviet Union. Its clear, concise treatment and practical advice make this an ideal reference for all researchers and consultants. Authors Priscilla E. Greenwood and Mikhail S. Nikulin demonstrate the application of these general purpose tests in a wide variety of specific settings. They also detail the various decisions to be made when applying Chi-squared tests to real data, and the proper application of these tests in standard hypothesis-testing situations; describe how Chi-squared type tests allow statisticians to construct a test statistic whose distribution is asymptotically Chi-squared, and to compute power against various alternatives; devote half of the book to examples of Chi-squared tests that can be easily adapted to situations not covered in the book; provide a self-contained, accessible treatment of the mathematical requisites; and include an extensive bibliography and suggestions for further reading.