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Cho, WKT and Gaines, BJ (2007)

Breaking the (Benford) law: Statistical fraud detection in campaign finance

American Statistician 61(3), pp. 218-223.

ISSN/ISBN: 0003-1305 DOI: 10.1198/000313007X223496

Abstract: Benford’s law is seeing increasing use as a diagnostic tool for isolating pockets of large data sets having irregularities that deserve closer inspection. Popular and academic accounts of campaign finance are rife with tales of corruption, but the complete data set of transactions for federal campaigns is enormous. Performing a systematic sweep is extremely arduous; hence, these data are a good candidate for initial screening by comparison to Benford’s distributions.

@article{doi:10.1198/000313007X223496, author = {Wendy K Tam Cho and Brian J Gaines}, title = {Breaking the (Benford) Law}, journal = {The American Statistician}, volume = {61}, number = {3}, pages = {218-223}, year = {2007}, publisher = {Taylor & Francis}, url = {}, doi = {10.1198/000313007X223496}, }

Reference Type: Journal Article

Subject Area(s): Accounting, Statistics