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Exploring Exploratory Data Analysis

2023-12-01Artigo científico Acesso aberto
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dc.contributor.authorBarsalou, Matthew
dc.contributor.authorSaraiva, Pedro Manuel
dc.contributor.authorHenriques, Roberto
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.pblSciendo
dc.date.accessioned2023-12-12T22:51:21Z
dc.date.available2023-12-12T22:51:21Z
dc.date.issued2023-12-01
dc.descriptionBarsalou, M., Saraiva, P. M., & Henriques, R. (2023). Exploring Exploratory Data Analysis: An Empirical Test of Run Chart Utility. Management Systems in Production Engineering, 31(4), 442-448. https://doi.org/10.2478/mspe-2023-0050
dc.description.abstractThis paper explores Exploratory Data Analysis (EDA). Graphical methods are used to gain insights in EDA and these insights can be useful for forming tentative hypotheses when performing a root cause analysis (RCA). The topic of EDA is well addressed in the literature; however, empirical studies of the efficacy of EDA are lacking. We therefore aim to evaluate EDA by comparing one group of students identifying salient features in a table against a second group of students attempting to identify salient features in the same data presented in the form of a run chart, and then extracting relevant conclusions from such a comparison. Two groups of students were randomly selected to receive data; either in the form of a table or a run chart. They were then tasked with visually identifying any data points that stood out as interesting. The number of correctly identified values and the time to find the values were both evaluated by a two-sample t-test to determine if there was a statistically significant difference. The participants with a graph found the correct values that stood out in the data much quicker than those that used a table. Those using the data in the form of a table too much longer and failed to identify values that stood out. However, those with a graph also had far more false positives. Much has been written on the topic of EDA in the literature; however, an empirical evaluation of this common methodology is lacking. This paper confirms with empirical evidence the effectiveness of EDA.en
dc.description.versionpublishersversion
dc.description.versionpublished
dc.format.extent7
dc.format.extent486977
dc.identifier.doi10.2478/mspe-2023-0050
dc.identifier.issn2299-0461
dc.identifier.otherPURE: 78168749
dc.identifier.otherPURE UUID: f4ff5fb4-c82e-4f41-8e35-163cbdda4256
dc.identifier.othercrossref: 10.2478/mspe-2023-0050
dc.identifier.otherScopus: 85179798161
dc.identifier.otherWOS: 001114518200009
dc.identifier.otherORCID: /0000-0002-4862-8177/work/152174891
dc.identifier.urihttp://hdl.handle.net/10362/161163
dc.identifier.urlhttps://www.scopus.com/pages/publications/85179798161
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:001114518200009
dc.identifier.urlhttps://www.sciendo.com/article/10.2478/mspe-2023-0050
dc.language.isoeng
dc.peerreviewedyes
dc.subjectExploratory Data Analysis
dc.subjectgraphs
dc.subjectroot cause analysis
dc.subjectproblem solving
dc.subjectManagement Information Systems
dc.subjectIndustrial and Manufacturing Engineering
dc.subjectManagement of Technology and Innovation
dc.titleExploring Exploratory Data Analysisen
dc.title.subtitleAn Empirical Test of Run Chart Utilityen
dc.typejournal article
degois.publication.firstPage442
degois.publication.issue4
degois.publication.lastPage448
degois.publication.titleManagement Systems in Production Engineering
degois.publication.volume31
dspace.entity.typePublication
rcaap.rightsopenAccess

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NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)