Preprint, posted September.
ISSN/ISBN: Not available at this time. DOI: 10.13140/RG.2.2.31321.75365/1
Abstract: Benford’s Law is applied as a method to analyze and find data manipulation in large datasets. It is consistently recognized as a valid method to combat financial fraud and tax evasion. Here, we studied its application to datasets of COVID-19, targeting data manipulation in the following: total confirmed cases, daily confirmed cases, total confirmed deaths, daily confirmed deaths. We considered countries among the most total confirmed cases on the day 1 September 2020 and China. General results showed that COVID-19’s numbers do follow Benford’s Law. Moreover, no evidence of data manipulation is seen for data from the USA, Brazil, India, Peru, South Africa, Colombia, Mexico, Spain, Argentina, Chile, the United Kingdom, France, Saudi Arabia, China, Philippines, Belgium, Pakistan, and Italy. Results suggest a high possibility of data manipulations for Russia’s data. A small divergence is present in Iran’s numbers.
Bibtex:
@misc{,
AUTHOR = {Anran Wei and Andre E. Vellwock},
TITLE = {Is COVID-19 data reliable? A statistical analysis with Benford's Law},
YEAR = {2020},
URL = {https://www.researchgate.net/publication/344164702_Is_COVID-19_data_reliable_A_statistical_analysis_with_Benford's_Law},
}
Reference Type: Preprint
Subject Area(s): Medical Sciences, Statistics, Voting Fraud