Spanish Journal of Statistics Vol. 5, No. 1, 2023, Pages 43-53.
ISSN/ISBN: Not available at this time. DOI: 10.37830/SJS.2023.1.03
Abstract: Most papers on Benford’s Law primarily discuss either (1) the science and mathematics for explaining the law; or (2) how to apply the law, especially for detecting data manipulation and fraud; or else (3) give suggestions for statistical tests to determine if data conform to a Benford’s distribution. Leonardo Campanelli’s recent paper “Testing Benford’s Law” objects to a descriptive measure I discussed in my earlier paper “The Promises and Pitfalls of Benford’s Law”—as if that measure were intended for Benford’s testing in the Category-3 sense relevant for Campanelli’s own paper. This reflects a conflation of meanings for “testing” that is unfortunately common in the Benford’s literature, wherein many Category-2 papers claim they are applying (directly) some conventional or new hypothesis test as as a tool to detect fraud. Yet, fraud detection is a forensic and context-sensitive process, for which there is no set formula. In this paper, I clarify the sampling plan I had used earlier to collect and analyze a quasi-random sample of datasets, based on published criteria in the literature, to paint a tentative picture of how far real data vary, and in what ways, from abstract BL expectations. Then, I discuss simulations I conducted subsequently to replicate and expand on my previous results.
Bibtex:
Not available at this time.
Reference Type: Journal Article
Subject Area(s): Social Sciences, Statistics