Applied adaptive statistical methods : tests of significance and confidence intervals /

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Bibliographic Details
Author / Creator:O'Gorman, Thomas W.
Imprint:Philadelphia, Pa. : Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104), 2004.
Description:1 electronic resource (xiii, 174 pages) : illustrations.
Language:English
Series:ASA-SIAM series on statistics and applied probability ; 12
ASA-SIAM series on statistics and applied probability ; 12.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12577643
Hidden Bibliographic Details
Varying Form of Title:Applied Adaptive Statistical Methods: Tests of Significance and Confidence Intervals
Other authors / contributors:Society for Industrial and Applied Mathematics.
ISBN:0898715539
9780898715538
9780898718430
0898718430
Notes:Title from title screen, viewed 10/20/2010.
Includes bibliographical references (pages 165-170) and index.
English.
Title page of print version.
Summary:Adaptive statistical tests, developed over the last 30 years, are often more powerful than traditional tests of significance, but have not been widely used. To date, discussions of adaptive statistical methods have been scattered across the literature and generally do not include the computer programs necessary to make these adaptive methods a practical alternative to traditional statistical methods. Until recently, there has also not been a general approach to tests of significance and confidence intervals that could easily be applied in practice. Modern adaptive methods are more general than earlier methods and sufficient software has been developed to make adaptive tests easy to use for many real-world problems. Applied Adaptive Statistical Methods: Tests of Significance and Confidence Intervals introduces many of the practical adaptive statistical methods developed over the last 10 years and provides a comprehensive approach to tests of significance and confidence intervals. It shows how to make confidence intervals shorter and how to make tests of significance more powerful by using the data itself to select the most appropriate procedure.
Other form:0898715539
Standard no.:SA12