Banks, DG (2000). Get M.A.D. with the Numbers! Moving Benford's Law from Art to Science. Fraud Magazine, September/October 2000.





Cho, WKT and Gaines, BJ (2007). Breaking the (Benford) law: Statistical fraud detection in campaign finance. American Statistician 61(3), pp. 218223. ISSN/ISBN:00031305. DOI:10.1198/000313007X223496.





Cinelli, C, Lins, R, Stachelek, J and Gorecki, J (2020). The Benford Analysis (benford.analysis) package . Posted on GitHub Repository; last accessed November 17, 2020.





Coeurjolly, JF (2020). Digit analysis for Covid19 reported data . Preprint arXiv:2005.05009 [stat.AP]; last accessed May 17, 2020.





Collins, JC (2017). Using Excel and Benford’s Law to detect fraud. Journal of Accountancy Feature/Technology Workshop, April 1.





Deckert, J, Myagkov, M and Ordeshook, PC (2010). The Irrelevance of Benford's Law for Detecting Fraud in Elections. CALTECH working paper 9.





Diekmann, A and Jann, B (2010). Benford’s Law and Fraud Detection: Facts and Legends. German Economic Review 11(3), pp. 397–401. DOI:10.1111/j.14680475.2010.00510.x.





Emerging Technology from the Arxiv (2015). How Benford’s Law Reveals Suspicious Activity on Twitter. Posted on the MIT Technology Review April 21; last accessed November 17, 2020.





Fewster, RM (2009). A Simple Explanation of Benford's Law. American Statistician 63(1), pp. 2632. DOI:10.1198/tast.2009.0005.





GómezCamponovo M, Moreno, J, Idrovo, ÁJ, Páez, M and Achkar, M (2016). Monitoring the Paraguayan epidemiological dengue surveillance system (20092011) using Benford's law. Biomédica 36, pp. 58392. DOI:10.7705/biomedica.v36i4.2731.





Goodman, WM (2016). The promises and pitfalls of Benford's law. Significance 13(3) pp. 3841. DOI:10.1111/j.17409713.2016.00919.x.





Hall, RC (2018). Why the Summation Test Results in a Benford, and not a Uniform Distribution, for Data that Conforms to a Log Normal Distribution. Preprint viXra.org > Number Theory > viXra:1809.0158; last accessed November 17, 2020.





Idrovo, AJ (2009). Benford's Law to evaluate the detection and reporting of cases during the A(H1N1) influenza outbreak. Rapid Response to: "The economic impact of pandemic influenza", BMJ 2009;339:b4888.





Idrovo, AJ, BojórquezChapela, I, FernándezNiño, JA and MorenoMontoya, J (2011). Performance of public health surveillance systems during the influenza A(H1N1) pandemic in the Americas: testing a new method based on Benford's Law. Epidemiol. Infect. 139(12), pp. 182734. ISSN/ISBN:14694409. DOI:10.1017/S095026881100015X.





Idrovo, AJ and ManriqueHernández, EF (2020). Data Quality of Chinese Surveillance of COVID19: Objective Analysis Based on WHO’s Situation Reports. Asia Pacific Journal of Public Health. DOI:10.1177/1010539520927265.





Jamain, A (2001). Benford’s Law. Master Thesis. Imperial College of London and ENSIMAG.





Joenssen, DW (2013). A New Test for Benford’s Distribution. In: AbstractProceedings of the 3rd Joint Statistical Meeting DAGStat, March 1822, 2013; Freiburg, Germany.





Judge, G and Schechter, L (2009). Detecting problems in survey data using Benford’s law. J. Human Resources 44, pp. 124. DOI:10.3368/jhr.44.1.1.





Koch, C and Okamura, K (2020). Benford's Law and COVID19 Reporting. Posted on SSRN April 28, 2020; last accessed November 17, 2020.





Lee, KB, Han, S and Jeong, Y (2020). COVID19, flattening the curve, and Benford’s law. Physica A: Statistical Mechanics and its Applications 559, 125090. DOI:10.1016/j.physa.2020.125090.





Nigrini, MJ (1999). I’ve got your number. Journal of Accountancy 187(5), pp. 7983.





Nigrini, MJ (2012). Benford's Law: Applications for Forensic Accounting, Auditing, and Fraud Detection . John Wiley & Sons: Hoboken, New Jersey. ISSN/ISBN:9781118152850. DOI:10.1002/9781119203094.





Nigrini, MJ and Miller, SJ (2009). Data Diagnostics Using SecondOrder Tests of Benford's Law. Auditing: A Journal of Practice & Theory 28(2), pp. 305324. DOI:10.2308/aud.2009.28.2.305
.





Peng, Y and Nagata, MH (2020). Statistical analysis of the Chinese COVID19 data with Benford's Law and clustering. Posted on LAMFO blog, Universidad de Brazilia on April 21, 2020; last accessed November 17, 2020.





Sambridge, M and Jackson, A (2020). National COVID numbers — Benford’s law looks for errors. Nature 581(7809), p. 384. DOI:10.1038/d41586020015655.





Smith, SW (1997). Explaining Benford's Law. Chapter 34 in: The Scientist and Engineer's Guide to Digital Signal Processing. California Technical Publishing: San Diego, CA. Republished in softcover by Newnes, 2002. ISSN/ISBN:0966017633.





Wei, A and Vellwock, AE (2020). Is COVID19 data reliable? A statistical analysis with Benford's Law. Preprint, posted September. DOI:10.13140/RG.2.2.31321.75365/1.




