打破本福德定律:利用欧几里得距离统计对COVID-19数据的统计分析

Q4 Mathematics

Statistics in Transition Pub Date : 2023-03-15 DOI:10.59170/stattrans-2023-028

L. Campanelli

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引用次数: 1

摘要

采用本福德定律的欧几里得距离统计检验，对各国每周新冠肺炎病例数进行了分析。在本研究考虑的100个国家和地区中，有62%的国家和地区在α = 0.05的显著水平上符合Benford定律，17%的国家和地区在0.01≤α < 0.05的显著水平上符合Benford定律，其余21%的国家和地区偏离Benford定律(p值小于0.01)。特别是，5%的国家“违反”本福德定律，p值小于0.001。

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Breaking Benford’s law: a statistical analysis of COVID-19 data using the Euclidean distance statistic

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.

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来源期刊

Statistics in Transition Decision Sciences-Statistics, Probability and Uncertainty

CiteScore

1.00

自引率

0.00%

发文量

审稿时长

9 weeks

期刊介绍： Statistics in Transition (SiT) is an international journal published jointly by the Polish Statistical Association (PTS) and the Central Statistical Office of Poland (CSO/GUS), which sponsors this publication. Launched in 1993, it was issued twice a year until 2006; since then it appears - under a slightly changed title, Statistics in Transition new series - three times a year; and after 2013 as a regular quarterly journal." The journal provides a forum for exchange of ideas and experience amongst members of international community of statisticians, data producers and users, including researchers, teachers, policy makers and the general public. Its initially dominating focus on statistical issues pertinent to transition from centrally planned to a market-oriented economy has gradually been extended to embracing statistical problems related to development and modernization of the system of public (official) statistics, in general.