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Farhadi, N (2021). Can we rely on COVID-19 data? An assessment of data from over 200 countries worldwide. Science Progress 104(2).

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Agyemang, EF, Mensah, JA and Nyarko, E (2023). How dependable is World Continental COVID-19 data? Disclosure of Inconsistencies in Daily Reportage Confirmed Cases, Recovered and Deaths During First Wave. Preprint – submitted to Heliyon. DOI:10.2139/ssrn.4516032. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Ali, A and Haque, S (2022). Application of Benford’s law to COVID-19 cases in selected countries of the Caribbean and globally. Caribbean Medical Journal. ISSN/ISBN:2664-5599. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Campanelli, L (2022). On the Euclidean distance statistic of Benford’s law. Communications in Statistics - Theory and Methods, pp. 1-24. DOI:10.1080/03610926.2022.2082480}. View Complete Reference Online information Works that this work references Works that reference this work
Campanelli, L (2022). Breaking Benford’s law: A statistical analysis of Covid-19 data using the Euclidean distance statistic. Preprint submitted to Statistics in Transition. View Complete Reference Online information Works that this work references Works that reference this work
Campanelli, L (2022). Monkeypox Obeys the (Benford's) Law: A Dynamic Analysis of Daily Case Counts in the United States of America. Preprint submitted to Statistics in Tran- sition new series.. View Complete Reference Online information Works that this work references Works that reference this work
Campanelli, L (2022). Tuning up the Kolmogorov-Smirnov test for testing Benford’s law. Preprint on ResearchGate. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Carmo, CRS, Nunes, FC and Caneppele, FdL (2023). The limits of conformity analysis under the Newcomb-Benford law and the COVID-19 pandemic in Brazil . Brazilian Journal of Biometrics 41, pp. 234-248 . DOI:10.28951/bjb.v41i3.626. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Cerqueti, R and Provenzano, D (2023). Benford's Law for economic data reliability: The case of tourism flows in Sicily. Chaos, Solitons & Fractals 173, p. 113635. DOI:10.1016/j.chaos.2023.113635. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Etim, ES, Daferighe, EE, Inyang, AB and Ekikor, ME (2023). Application of Benford’s Law and the Detection of Accounting Data Fraud in Nigeria. International Journal of Auditing and Accounting Studies 5(2) pp. 119-163. DOI:10.47509/IJAAS.2023.v05i02.01. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Farhadi, N and Lahooti, H (2021). Are COVID-19 Data Reliable? A Quantitative Analysis of Pandemic Data from 182 Countries. COVID 1, pp. 137–152. DOI:10.3390/covid1010013. View Complete Reference Online information Works that this work references Works that reference this work
Farhadi, N and Lahooti, H (2021). Pandemic Growth and Benfordness: Empirical Evidence from 176 Countries Worldwide. COVID 1(1), pp. 366-383. DOI:10.3390/covid1010031. View Complete Reference Online information Works that this work references Works that reference this work
Farhadi, N and Lahooti, H (2022). Forensic Analysis of COVID-19 Data from 198 Countries Two Years after the Pandemic Outbreak. COVID 2(4), pp. 472-484. DOI:10.3390/covid2040034. View Complete Reference Online information Works that this work references Works that reference this work
Farhadi, N and Lahooti, H (2022). In Data We Trust: Proving Market Manipulation on the Tehran Stock Exchange. International Journal of Business and Management 17(4). DOI:10.5539/ijbm.v17n4p1. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Filho, TMR, Mendes, JFF, Lucio, ML and Moret, MA (2022). Reliability of COVID-19 data and government policies. Preprint arXiv:2208.11226 [physics.soc-ph]; last accessed August 31, 2022. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Filho, TMR, Mendes, JFF, Lucio, ML and Moret, MA (2023). COVID-19 data, mitigation policies and Newcomb–Benford law. Chaos, Solitons and Fractals 174 p. 113814. DOI:10.1016/j.chaos.2023.113814. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Us, D (2021). Benford's Law: An Empirical Analysis of Reported Covid-19 Cases and Institutional Structures Around the Globe . Undergraduate Thesis, Università commerciale Luigi Bocconi, Milan. DOI:10.13140/RG.2.2.28839.88488. View Complete Reference Online information Works that this work references Works that reference this work
Youkta, K, Paramanik, RN and Nupur, S (2023). Does Digital Awareness Reduce Misreporting of Covid-19 Data? An Empirical Investigation. Review of Economic Analysis 15(3-4), pp. 271-283. View Complete Reference Online information Works that this work references No Bibliography works reference this work
Zenkov, AV (2021). Stylometry and Numerals Usage: Benford’s Law and Beyond. Stats 4(4), pp. 1051-1068. ISSN/ISBN:2571-905X. DOI:10.3390/stats4040060. View Complete Reference Online information Works that this work references Works that reference this work