Nonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book presents SAS and R programs, allowing readers to carry out the different statistical methods, such as permutation and bootstrap tests. The author considers example data sets in each chapter to illustrate methods. Numerous real-life data from various areas, including the bible, and their analyses provide for greatly diversified reading.
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Although the major development of nonparametric methods came to a certain end in the 1970s, their importance undoubtedly persists. What is still needed is a computer assisted evaluation of their main properties. This book closes that gap.
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Markus Neuhauser
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Condición: New. Markus NeuhauserNonparametric Statistical Tests: A Computational Approach describes classical nonparametric tests, as well as novel and little-known methods such as the Baumgartner-Weiss-Schindler and the Cucconi tests. The book pres. Nº de ref. del artículo: 869719563
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Buch. Condición: Neu. Neuware - This book provides a modern and accessible overview of computationally-intensive nonparametric statistical methods. Presenting up-to-date and detailed information, the text focuses on the use of permutation and bootstrap methods to assess the significance of a statistic in a hypothesis test. It includes numerous real examples to illustrate the methods, and SAS programs are used throughout to apply them. In addition, a significant portion of the book is devoted to (recent) nonparametric tests for the comparison of independent groups with potentially unequal variances. Nº de ref. del artículo: 9781439867037
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