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Chapter 3 - Benford’s Law and Assessing Conformity

Published online by Cambridge University Press:  09 November 2023

Michael A. Long ,
Paul B. Stretesky ,
Kenneth J. Berry ,
Janis E. Johnston  and
Michael J. Lynch
Michael A. Long
Affiliation:
Oklahoma State University
Paul B. Stretesky
Affiliation:
Northumbria University, Newcastle
Kenneth J. Berry
Affiliation:
Colorado State University
Janis E. Johnston
Affiliation:
USDA
Michael J. Lynch
Affiliation:
University of South Florida
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Summary

Chapter 3 describes and illustrates the Benford probability distribution. A brief summary of the origin and evolution of the Benford distribution is drawn and the development and assessment of various measures of goodness of fit between an empirical distribution and the Benford distribution are described and illustrated. These masures are Pearson’s chi-squared, Wilks’ likelihood-ratio, Hardy and Ramanujan’s partition theory, Fisher’s exact test, Kuiper’s measure, Tam Cho and Gaines’ d measure, Cohen’s w measure, and Nigrini’s MAD measure.

Keywords

assessing conformityBenford distributionBenford’s laweffect sizepermutation statistical methodsvalidity
Type
Chapter
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Applying Benford's Law for Assessing the Validity of Social Science Data , pp. 24 - 73
Publisher: Cambridge University Press
Print publication year: 2023

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