Open Source Web-Based Software to Evaluate Normal Distribution: Normality Assessment Software

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dc.authorscopusid57188684428
dc.authorscopusid57211715860
dc.authorscopusid11738942300
dc.contributor.authorArslan A.K.
dc.contributor.authorTunc Z.
dc.contributor.authorColak C.
dc.date.accessioned2024-08-04T20:04:00Z
dc.date.available2024-08-04T20:04:00Z
dc.date.issued2019
dc.departmentİnönü Üniversitesien_US
dc.description3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 -- 11 October 2019 through 13 October 2019 -- 156063en_US
dc.description.abstractIn this study, it was aimed to develop a new user-friendly web-based software that would easily test single-variable univariate and multivariate normal distribution suitability and enable users to get more accurate results in their studies.Shiny, an open source R package, was used to develop the proposed web software. In the developed software, Shapiro-Wilk and Anderson-Darling tests were used for the uniformity of univariate distribution, and Mardia's skewness-kurtosis, Henze-Zircon and Doornik-Hansen tests were used for multivariate normal distribution. Outputs for conformity to normal distribution were supported by using graphical methods. In practice, for the data set where each variable consisting of two variables derived by simulation has a standard normal distribution and the variables contain 1000 observations, the normal distribution conformity analysis has been performed. In the derived data set, each variable is normally distributed according to the Anderson-Darling and Shapiro-Wilk tests.In addition, the derived data set showed normal distribution with three variables according to Mardia's skewness-kurtosis and Henze-Zirkler tests. However, according to the Doornik-Hansen test, the triple does not show normal distribution.The developed software is a new user-friendly web-based software that can easily perform univariate and multivariate normal distribution conformity analysis and enable users to get more accurate results in their work. In further studies, Type I and Type II error types are planned to be included in the software in order to determine the best method. © 2019 IEEE.en_US
dc.identifier.doi10.1109/ISMSIT.2019.8932909
dc.identifier.isbn9781728137896
dc.identifier.scopus2-s2.0-85078020099en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISMSIT.2019.8932909
dc.identifier.urihttps://hdl.handle.net/11616/92255
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof3rd International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2019 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectnormal distributionen_US
dc.subjectsimulationen_US
dc.subjectweb-based softwareen_US
dc.titleOpen Source Web-Based Software to Evaluate Normal Distribution: Normality Assessment Softwareen_US
dc.title.alternativeNormal Dagilima Uygunlugu Degerlendirmek Icin Acik Kaynak Web Tabanli Yazilim: Normal Dagilimi Inceleme Yazilimien_US
dc.typeConference Objecten_US

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