A Guide to Chi-Squared Testing (Wiley Series in Probability and Statistics)
Language: English
Published by Wiley-Interscience, 1996
Series: Book 152 of 358 - Wiley Series in Probability and Statistics
- Hardcover
- New
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In English.
Seller Inventory # ria9780471557791_new
- Title
- A Guide to Chi-Squared Testing (Wiley Series in Probability and Statistics)
- Author
- Greenwood, Priscilla E.; Nikulin, Michael S.
- Publisher
- Wiley-Interscience
- Publication year
- 1996
- Condition
- New
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 047155779X
- ISBN 13
- 9780471557791
- Series
- Book 152 of 358: Wiley Series in Probability and Statistics
The first step-by-step guide to conducting successful Chi-squaredtests
Chi-squared testing is one of the most commonly applied statisticaltechniques. It provides reliable answers for researchers in a widerange of fields, including engineering, manufacturing, finance,agriculture, and medicine.
A Guide to Chi-Squared Testing brings readers up to date on recentinnovations and important material previously published only in theformer Soviet Union. Its clear, concise treatment and practicaladvice make this an ideal reference for all researchers andconsultants.
Authors Priscilla E. Greenwood and Mikhail S. Nikulin demonstratethe application of these general purpose tests in a wide variety ofspecific settings. They also
* Detail the various decisions to be made when applying Chi-squaredtests to real data, and the proper application of these tests instandard hypothesis-testing situations
* Describe how Chi-squared type tests allow statisticians toconstruct a test statistic whose distribution is asymptoticallyChi-squared, and to compute power against various alternatives
* Devote half of the book to examples of Chi-squared tests that canbe easily adapted to situations not covered in the book
* Provide a self-contained, accessible treatment of themathematical requisites
* Include an extensive bibliography and suggestions for furtherreading
Chi-squared testing is one of the most commonly applied statisticaltechniques. It provides reliable answers for researchers in a widerange of fields, including engineering, manufacturing, finance,agriculture, and medicine.
A Guide to Chi-Squared Testing brings readers up to date on recentinnovations and important material previously published only in theformer Soviet Union. Its clear, concise treatment and practicaladvice make this an ideal reference for all researchers andconsultants.
Authors Priscilla E. Greenwood and Mikhail S. Nikulin demonstratethe application of these general purpose tests in a wide variety ofspecific settings. They also
* Detail the various decisions to be made when applying Chi-squaredtests to real data, and the proper application of these tests instandard hypothesis-testing situations
* Describe how Chi-squared type tests allow statisticians toconstruct a test statistic whose distribution is asymptoticallyChi-squared, and to compute power against various alternatives
* Devote half of the book to examples of Chi-squared tests that canbe easily adapted to situations not covered in the book
* Provide a self-contained, accessible treatment of themathematical requisites
* Include an extensive bibliography and suggestions for furtherreading
"Synopsis" may belong to another edition of this title.
About the Author
Priscilla E. Greenwood is Professor of Mathematics at the University of British Columbia, Vancouver, Canada. A Fellow of the Institute of Mathematical Statistics, she received her PhD in mathematics from the University of Wisconsin.
Mikhail S. Nikulin is Professor of Statistics at The University Bordeaux 2 and a member of The Laboratory of Statistical Methods of the Steklov Mathematical Institute at St. Petersburg. He earned his doctorate in the Theory of Probability and Mathematical Statistics from The Steklov Mathematical Institute in Moscow.
Mikhail S. Nikulin is Professor of Statistics at The University Bordeaux 2 and a member of The Laboratory of Statistical Methods of the Steklov Mathematical Institute at St. Petersburg. He earned his doctorate in the Theory of Probability and Mathematical Statistics from The Steklov Mathematical Institute in Moscow.
"About the title" may belong to another edition of this title.
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