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Resampling Based Multiple Testing Examples by Westfall Peter (11 results)
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hardcover. Condition: Very Good. 1st Edition. Used - Very Good.
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Resampling-based multiple testing examples and methods for P-value adjustment Peter H. Westfall, S. Stanley Young. Wiley publications in statistics Applied statistics.
Published by New York, Wiley [1993]., 1993
ISBN 10: 0471557617 ISBN 13: 9780471557616
Language: English
Hardcover. Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 62 WES 9780471557616 Sprache: Englisch Gewicht in Gramm: 1150.
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Hardcover. Condition: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
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Condition: New. SUPER FAST SHIPPING.
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Resampling-Based Multiple Testing : Examples and Methods for P-Value Adjustment
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Resampling-Based Multiple Testing: Examples and Methods for p-Value Adjustment
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Condition: As New. Unread book in perfect condition.
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Resampling-Based Multiple Testing : Examples and Methods for P-Value Adjustment
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Buch. Condition: Neu. Neuware - Combines recent developments in resampling technology (including the bootstrap) with new methods for multiple testing that are easy to use, convenient to report and widely applicable. Software from SAS Institute is available to execute many of the methods and programming is straightforward for other applications. Explains how to summarize results using adjusted p-values which do not necessitate cumbersome table look-ups. Demonstrates how to incorporate logical constraints among hypotheses, further improving power.
