Modified unbiased estimators for population variance: An application for COVID-19 deaths in Russia


CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, vol.34, no.22, 2022 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 34 Issue: 22
  • Publication Date: 2022
  • Doi Number: 10.1002/cpe.7169
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, zbMATH, Civil Engineering Abstracts
  • Keywords: COVID-19, death number, Hartley-Ross type estimator, unbiased estimator, variance estimator
  • Hacettepe University Affiliated: Yes


The article deal with the class unbiased forms of the variance estimators using Hartley-Ross type in the simple random sampling. The mean squared error (since it is an unbiased estimator, variance is calculated) of the suggested, up to the first order of approximation, is derived. The proposed estimator using COVID-19 data in Russia has been proven to be more efficient than the considered estimators under the conditions. Thus, it allows us to see the variance estimator that best predicts the change according to federal regions in Russia's number of COVID-19 deaths. This study also provides an unbiased family of estimators that are more efficient than existing estimators, which estimate the variance of the total death number of COVID-19 based on the daily new cases number. The most important difference of this article from other studies in the literature is that it is the first study to examine the variance of the COVID-19 cumulative mortality value in terms of variance estimation using the simple random sampling method with the auxiliary variable.