About: Digit analysis for Covid-19 reported data

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Digit analysis for Covid-19 reported data
Creator	Coeurjolly, Jean-François
source	ArXiv
abstract	The coronavirus which appeared in December 2019 in Wuhan has spread out worldwide and caused the death of more than 280,000 people (as of May, 11 2020). Since February 2020, doubts were raised about the numbers of confirmed cases and deaths reported by the Chinese government. In this paper, we examine data available from China at the city and provincial levels and we compare them with Canadian provincial data, US state data and French regional data. We consider cumulative and daily numbers of confirmed cases and deaths and examine these numbers through the lens of their first two digits and in particular we measure departures of these first two digits to the Newcomb-Benford distribution, often used to detect frauds. Our finding is that there is no evidence that cumulative and daily numbers of confirmed cases and deaths for all these countries have different first or second digit distributions. We also show that the Newcomb-Benford distribution cannot be rejected for these data.
has issue date	2020-05-11(xsd:dateTime)
has license	arxiv
sha1sum (hex)	944f0fc00cc8210c35138b5468e4227a54623546
resource representing a document's title	Digit analysis for Covid-19 reported data
resource representing a document's body	covid:944f0fc00cc8210c35138b5468e4227a54623546#body_text
is schema:about of	named entity 'digits' named entity 'confirmed' named entity 'distribution' named entity 'data' named entity 'Digit' »more»

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