Citation link: http://dx.doi.org/10.25819/ubsi/2961
Files in This Item:
File Description SizeFormat
New_Perspectives_on_Statistical_Data_Analysis.pdf474.76 kBAdobe PDFThumbnail
View/Open
Dokument Type: InProceedings
metadata.dc.title: New perspectives on statistical data analysis: challenges and possibilities of digitalization for hypothesis testing in quantitative research
Authors: Kelter, Riko  
Institute: Forschungskolleg “Institute for Advanced Study” (FoKos) 
Free keywords: Data Analysis, Statistical Inference, Bayesian Statistics, Hypothesis Testing, Mathematical Psychology, Statistische Schlussfolgerung, Bayessche Statistik, Prüfung von Hypothesen
Dewey Decimal Classification: 004 Informatik
GHBS-Clases: QGT
Issue Date: 2020
Publish Date: 2020
Source: Radtke, 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 - 108
Abstract: 
p-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.
DOI: http://dx.doi.org/10.25819/ubsi/2961
URN: urn:nbn:de:hbz:467-16426
URI: https://dspace.ub.uni-siegen.de/handle/ubsi/1642
License: http://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections:Publikationen aus der Universität Siegen

This item is protected by original copyright

Show full item record

Page view(s)

503
checked on Mar 29, 2024

Download(s)

251
checked on Mar 29, 2024

Google ScholarTM

Check

Altmetric


This item is licensed under a Creative Commons License Creative Commons