Citation link: http://dx.doi.org/10.25819/ubsi/2961
DC FieldValueLanguage
crisitem.author.orcid0000-0001-9068-5696-
dc.contributor.authorKelter, Riko-
dc.date.accessioned2020-11-10T12:12:52Z-
dc.date.available2020-11-10T12:12:52Z-
dc.date.issued2020de
dc.description.abstractp-values, the 'gold standard' of statistical validity are not as reliable as many scientists assume. In the last decade, severe problems have been observed regarding the validity of highly reputable research. Additionally, the growing availability of big data challenges the design and statistical analysis of studies and experiments across science. Therefore, it is more important than ever to make the best use of available computational tools, software and possibilities digitalization offers to improve the validity of research results. In this paper, we focus on an essential procedure often carried out in quantitative research, which is directly related to the experienced problems: Statistical hypothesis testing. First, we show that the traditional way of hypothesis testing has severe logical problems. Second, it is shown that due to the increasing availability of computational resources, highly sophisticated methods from the area of computational statistics - namely Bayesian data analysis - can complement and even replace traditional hypothesis testing. Third, we highlight how digitalization helps in making these technologies available to a vast range of researchers in the form of the novel and free software package JASP. Together, this paper shows that considering a change in perspective on statistical data analysis, in particular on hypothesis testing, provides the possibility to improve the transparency and reliability of research in the medical, social and natural sciences.en
dc.identifier.doihttp://dx.doi.org/10.25819/ubsi/2961-
dc.identifier.urihttps://dspace.ub.uni-siegen.de/handle/ubsi/1642-
dc.identifier.urnurn:nbn:de:hbz:467-16426-
dc.language.isoende
dc.relation.conferenceGet together – Think together! - Nachwuchstagung zur Digitalisierungsforschung an der Universität Siegen, 21.04.2020, Siegende
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceRadtke, Jörg (Hrsg.) ; Klesel, Michael (Hrsg.) ; Niehaves, Björn (Hrsg.): New perspectives on digitalization: Local issues and global impact. Siegen: Universitätsbibliothek Siegen, 2020. - DOI http://dx.doi.org/10.25819/ubsi/1894, S. 100 - 108de
dc.subject.ddc004 Informatikde
dc.subject.otherData Analysisen
dc.subject.otherStatistical Inferenceen
dc.subject.otherBayesian Statisticsen
dc.subject.otherHypothesis Testingen
dc.subject.otherMathematical Psychologyen
dc.subject.otherStatistische Schlussfolgerungde
dc.subject.otherBayessche Statistikde
dc.subject.otherPrüfung von Hypothesende
dc.subject.swbDatenanalysede
dc.subject.swbStatistikde
dc.subject.swbMathematische Psychologiede
dc.titleNew perspectives on statistical data analysis: challenges and possibilities of digitalization for hypothesis testing in quantitative researchen
dc.typeInProceedingsde
item.fulltextWith Fulltext-
ubsi.origin.dspace51-
ubsi.publication.affiliationForschungskolleg “Institute for Advanced Study” (FoKos)de
ubsi.source.authorRadtke, Jörgde
ubsi.source.authorKlesel, Michaelde
ubsi.source.authorNiehaves, Björnde
ubsi.source.conference-end21.04.2020de
ubsi.source.conference-placeSiegende
ubsi.source.conference-start21.04.2020de
ubsi.source.conference-titleGet together – Think together! - Nachwuchstagung zur Digitalisierungsforschung an der Universität Siegende
ubsi.source.doihttp://dx.doi.org/10.25819/ubsi/1894-
ubsi.source.issued2020de
ubsi.source.pagefrom100de
ubsi.source.pageto108de
ubsi.source.placeSiegende
ubsi.source.publisherUniversitätsbibliothek Siegende
ubsi.source.titleNew perspectives on digitalization: Local issues and global impactde
ubsi.subject.ghbsQGTde
Appears in Collections:Publikationen aus der Universität Siegen
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