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dc.contributor.authorZogheib, Bashar
dc.date.accessioned2020-04-10T14:16:58Z
dc.date.available2020-04-10T14:16:58Z
dc.date.issued2018
dc.identifier.urihttp://jbe.tums.ac.ir/index.php/jbe/article/view/205
dc.identifier.urihttps://dspace.auk.edu.kw/handle/11675/5751
dc.description.abstractThe sample standard deviation S is the common point estimator of σ, but S is sensitive to the presence of outliers and may not be an efficient estimator of σ in skewed and leptokurtic distributions. Although S has good efficiency in platykurtic and moderately leptokurtic distributions, its classical inferential methods may perform poorly in non-normal distributions. The classical confidence interval for σ relies on the assumption of normality of the distribution. In this paper, a performance comparison of six confidence interval estimates of σ is performed under ten distributions that vary in skewness and kurtosis.
dc.publisherJournal of Biostatistics and Epidemiology
dc.relation.journalJournal of Biostatistics and Epidemiology
dc.titleImproved confidence interval estimation of the population standard deviation using ranked set sampling: A simulation study
dc.typeJournal Article
dcterms.bibliographicCitationAlbatineh, A., Wilcox, M., Zogheib, B., & Kibria, G. (2018). Improved confidence interval estimation of the population standard deviation using ranked set sampling: A simulation study. Journal of Biostatistics and Epidemiology, 4(3), 173-183. Retrieved from http://jbe.tums.ac.ir/index.php/jbe/article/view/205
dc.journal.volume4
dc.journal.issue3
dc.article.pages173-183


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