Abstract Details
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Activity Number:
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699
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Type:
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Contributed
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Date/Time:
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Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Education
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| Abstract - #307678 |
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Title:
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A Note on Quantifying Measure of Belief in a Significance Testing Problem
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Author(s):
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Andrew Neath*+
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Companies:
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SIU Edwardsville
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Keywords:
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Bayes factor ;
likelihood ratio ;
false discovery rate ;
p-value
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Abstract:
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Significance testing is commonly taught to introductory students as a data analytical tool for determining when a scientific hypothesis can be accepted as the true state of nature. Despite its popularity, however, the significance testing approach is ill-equipped for handling the problem of quantifying evidence. In this paper, we illustrate how the use of significance testing for providing a measure of belief in a hypothesis test result is contradictory to good scientific principles.
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Authors who are presenting talks have a * after their name.
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