A Guide to Chi-Squared Testing

Передня обкладинка
John Wiley & Sons, 5 квіт. 1996 р. - 304 стор.
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

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The ChiSquared Test of Pearson 1 Pearsons Statistic
Some Recommendations When n is Small
Chisquared Test Against a Simple Alternative
The Continuity Correction for Pearsons Test with One Degree of Freedom and the 2 x 2 Table
Chisquared Test for Randomness of a Sample
How Many Classes?
Other Measures of Fit
Pearsons Statistic and the Theory of Estimation
Distribution of Test Statistic Again Depends on Method of Estimation
A Modification of Pearsons Statistic
The Chisquared Test for Continuous Distributions with Location and Scale Parameters
The Chisquared Test for an Exponential Family
Some Additional Examples
Multivariate Normal and Chisquared Distributions

Fishers Theorem
Distribution of the Test Statistic Depends on Method of Estimation

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Asymptotic Statistics
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Обмежений попередній перегляд - 2000
Exact Analysis of Discrete Data
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Обмежений попередній перегляд - 2005
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Про автора (1996)

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.

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