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Nonparametric Statistics: An Introduction (Quantitative Applications in the Social Sciences) - Softcover
Synopsis
Through the use of actual research investigations that have appeared in recent social science journals, Gibbons shows the reader the specific methodology and logical rationale for many of the best-known and most frequently used nonparametric methods that are applicable to most small and large sample sizes. The methods are organized according to the type of sample structure that produced the data to be analyzed, and the inference types covered are limited to location tests, such as the sign test, the Mann-Whitney-Wilcoxon test, the Kruskal-Wallis test and Friedman′s test. The formal introduction of each test is followed by a data example, calculated first by hand and then by computer.
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About the Author
Gibbons, a retired professor from the University of Alabama who now lives in Florida, earned her Ph.D. in statistics from Virginia Tech in 1962. She says she made the gift as an effort to enable the university to recruit the nation’s best doctoral candidates in her field, and to help the United States remain the global leader in the discipline.
“Statistics is my love,” Gibbons said. “It’s my vocation, as well as my avocation. I was so delighted when I discovered statistics ... and I think that it is a field that will always be of utmost importance.”
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- PublisherSAGE Publications, Inc
- Publication date1992
- ISBN 10 0803939515
- ISBN 13 9780803939516
- BindingPaperback
- LanguageEnglish
- Edition number1
- Number of pages96
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Nonparametric Statistics : An Introduction
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Nonparametric Statistics : An Introduction
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