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Measuring statistical evidence using relative belief / Michael Evans.

By: Material type: TextTextSeries: Monographs on statistics and applied probability ; 144Publication details: Boca Raton : CRC Press, ©2015.Description: xvii, 232 p. : illustrations ; 25 cmISBN:
  • 9781482242799 (alk. paper)
Subject(s): DDC classification:
  • 000SA.1 23 Ev92
Contents:
1. Statistical problems -- 2. Probability -- 3. Characterizing statistical evidence -- 4. Measuring statistical evidence using relative belief -- 5. Choosing and checking the model and prior -- 6. Conclusions.
Summary: The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 000SA.1 Ev92 (Browse shelf(Opens below)) Available 137276
Total holds: 0

Includes bibliographical references and index.

1. Statistical problems --
2. Probability --
3. Characterizing statistical evidence --
4. Measuring statistical evidence using relative belief --
5. Choosing and checking the model and prior --
6. Conclusions.

The book attempts to establish a gold standard for how a statistical analysis should proceed. It first introduces basic features of the overall approach, such as the roles of subjectivity, objectivity, infinity, and utility in statistical analyses. It next discusses the meaning of probability and the various positions taken on probability. The author then focuses on the definition of statistical evidence and how it should be measured. He presents a method for measuring statistical evidence and develops a theory of inference based on this method. He also discusses how statisticians should choose the ingredients for a statistical problem and how these choices are to be checked for their relevance in an application.

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