Issues in Information Systems 21(2), pp. 238-247.
ISSN/ISBN: Not available at this time. DOI: Not available at this time.
Abstract: This paper attempts to determine whether precinct level election data conforms with Benford’s Law. In order to evaluate whether election data conform with Benford’s Law, we constructed a two-part test. The first test assesses whether election data correlates with Benford’s law. If the election data under study is found to correlate with Benford’s law, we then subject it to the Kolmogorov-Smirnov test, which is used to evaluate more rigorous conformance with Benford’s law and which aids in forensic analysis. We conclude that the frequency pattern of the first digits of the precinct level elections under study correlate strongly with the pattern predicted by Benford’s Law of first digits. We also conclude, however, that the correlation is not strong enough for definitive forensic analysis.
Bibtex:
@article{,
author = {Ellen Friedman and Rajkumar Kolakaluri and Manjeet Rege},
title = {Benford’s Law Applied to Precinct Level Election Data},
year = {2020},
journal = {Issues in Information Systems},
volume = {21},
issue = {2},
pages = {238--247},
url = {http://www.iacis.org/iis/2020/2_iis_2020_238-247.pdf},
}
Reference Type: Journal Article
Subject Area(s): Statistics, Voting Fraud