Breaking Benford's Law: a Statistical Analysis of COVID-19 Data Using the Euclidean Distance Statistic

• Autorzy: Leonardo Campanelli
• Języki publikacji: EN

Abstrakty

EN

Using the Euclidean distance statistical test of Benford's law, we analyse the COVID-19 weekly case counts by country. While 62% of the 100 countries and territories considered in the present study conforms to Benford's law at a significant level of α = 0.05 and 17% at a significant level of 0.01 ≤ α < 0.05, the remaining 21% shows a deviation from it (p values smaller than 0.01). In particular, 5% of the countries 'break' Benford's law with a p value smaller than 0.001. (original abstract)

Słowa kluczowe

EN

COVID-19; Benford's Law; Data analysis

PL

COVID-19; Prawo Benforda; Analiza danych

• Czasopismo: Statistics in Transition
• Rocznik: 2023
• Tom: 24
• Numer: nr 2
• Strony: 201--215

Twórcy

autor

Leonardo Campanelli

• All Saints University School of Medicine, Toronto, Canada

Bibliografia

• Benford, F., (1938). The Law of Anomalous Numbers. Proceedings of the American Physical Society 78, pp. 551-572.
• Campanelli, L., (2021). On the Euclidean Distance Statistic of Benford's Law. Communications in Statistics - Theory and Methods. DOI: 10.1080/03610926.2022.2082480.
• Campanelli, L., (2022). Testing Benford's Law: from small to very large data sets. Submitted to Spanish Journal of Statistics.
• Cho, W. K. T., Gaines, B. J., (2007). Breaking the (Benford) Law: Statistical Fraud Detection in Campaign Finance. Am. Stat. 61, pp. 218-223.
• Facchinetti, S., (2009). A procedure to find exact critical values of Kolmogorov-Smirnov test, Ital. J. Appl. Stat. 21, pp. 337-359.
• Farhadi, N., (2021). Can we rely on COVID-19 data? An assessment of data from over 200 countries worldwide. Sci. Prog. 104, pp. 1-19.
• Goodman, W., (2016). The promises and pitfalls of Benford's law. Significance 13, pp. 38-41.
• Hill, T. P., (1995a). The significant-digit phenomenon. Am. Math. Mon. 102, pp. 322-327.
• Hill, T. P., (1995b). Base-invariance implies Benford's law. Proc. Am. Math. Soc. 123, pp. 887-895.
• Hill, T. P., (1995c). A statistical derivation of the significant-digit law. Stat. Sci. 10, 354- 363.
• International Health Regulations, (2005). The document can be observed at https://www.who.int.
• John Hopkin University, (2021). https://www.ghsindex.org.
• Leemis, L. M., Schmeiser, B. W., Evans, D. L., (2000). Survival Distributions Satisfying Benford's Law. Am. Stat. 54, pp. 236-241.
• Miller, S. J. (ed.), 2015. Benford's Law: Theory and Applications. Princeton. Princeton University Press.
• Morrow, J., (2014). Benford's Law, Families of Distributions and a Test Basis. London: Centre for Economic Performance.
• Newcomb, S., (1881). Note on the frequency of use of different digits in natural numbers. Am. J. Math. 4, pp. 39-40.
• Nigrini, M., (1996). A taxpayer compliance application of Benford's law. Journal of the American Taxation Association 18, pp. 72-91.
• Noether, G. E., (1963). Note on the Kolmogorov statistic in the discrete case. Metrika 7, pp. 115-116.
• Pérez-González, F., Abdallah, C. T., Heileman, G. L., (2007). Benford's Law in Image Processing. IEEE International Conference on Image Processing, pp. 405--408.
• Roukema, B. F., (2013). A first-digit anomaly in the 2009 Iranian presidential election. J. Appl. Stat. 41:1, pp. 164-199.
• Sambridge, M., Tkalˇci´c, N., Jackson, A., (2010). Benford's law in the natural sciences. Geophys. Res. Lett. 37, L22301.
• Sambridge, M., Jackson, A., (2020). National COVID numbers - Benford's law looks for errors. Nature 581, p. 384.
• Wei, A. and Vellwock, A. E., (2020). Is COVID-19 data reliable? A statistical analysis with Benford's law. DOI: 10.13140/RG.2.2.31321.75365/1.
• World Health Organization, (2021). https://www.covid19.who.int.

Identyfikatory

DOI

10.59170/stattrans-2023-028