Exploring Exploratory Data Analysis
| Autor(a) principal: | |
|---|---|
| Data de Publicação: | 2023 |
| Outros Autores: | , |
| Tipo de documento: | Artigo |
| Idioma: | eng |
| Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
| Texto Completo: | http://hdl.handle.net/10362/161163 |
Resumo: | Barsalou, 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 |
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Exploring Exploratory Data AnalysisAn Empirical Test of Run Chart UtilityExploratory Data Analysisgraphsroot cause analysisproblem solvingManagement Information SystemsIndustrial and Manufacturing EngineeringManagement of Technology and InnovationBarsalou, 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-2023-0050This 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.Information Management Research Center (MagIC) - NOVA Information Management SchoolNOVA Information Management School (NOVA IMS)RUNBarsalou, MatthewSaraiva, Pedro ManuelHenriques, Roberto2023-12-12T22:51:21Z2023-12-012023-12-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article7application/pdfhttp://hdl.handle.net/10362/161163eng2299-0461PURE: 78168749https://doi.org/10.2478/mspe-2023-0050info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-03-11T05:43:58Zoai:run.unl.pt:10362/161163Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:58:23.730978Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
| dc.title.none.fl_str_mv |
Exploring Exploratory Data Analysis An Empirical Test of Run Chart Utility |
| title |
Exploring Exploratory Data Analysis |
| spellingShingle |
Exploring Exploratory Data Analysis Barsalou, Matthew Exploratory Data Analysis graphs root cause analysis problem solving Management Information Systems Industrial and Manufacturing Engineering Management of Technology and Innovation |
| title_short |
Exploring Exploratory Data Analysis |
| title_full |
Exploring Exploratory Data Analysis |
| title_fullStr |
Exploring Exploratory Data Analysis |
| title_full_unstemmed |
Exploring Exploratory Data Analysis |
| title_sort |
Exploring Exploratory Data Analysis |
| author |
Barsalou, Matthew |
| author_facet |
Barsalou, Matthew Saraiva, Pedro Manuel Henriques, Roberto |
| author_role |
author |
| author2 |
Saraiva, Pedro Manuel Henriques, Roberto |
| author2_role |
author author |
| dc.contributor.none.fl_str_mv |
Information Management Research Center (MagIC) - NOVA Information Management School NOVA Information Management School (NOVA IMS) RUN |
| dc.contributor.author.fl_str_mv |
Barsalou, Matthew Saraiva, Pedro Manuel Henriques, Roberto |
| dc.subject.por.fl_str_mv |
Exploratory Data Analysis graphs root cause analysis problem solving Management Information Systems Industrial and Manufacturing Engineering Management of Technology and Innovation |
| topic |
Exploratory Data Analysis graphs root cause analysis problem solving Management Information Systems Industrial and Manufacturing Engineering Management of Technology and Innovation |
| description |
Barsalou, 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 |
| publishDate |
2023 |
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2023-12-12T22:51:21Z 2023-12-01 2023-12-01T00:00:00Z |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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publishedVersion |
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http://hdl.handle.net/10362/161163 |
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http://hdl.handle.net/10362/161163 |
| dc.language.iso.fl_str_mv |
eng |
| language |
eng |
| dc.relation.none.fl_str_mv |
2299-0461 PURE: 78168749 https://doi.org/10.2478/mspe-2023-0050 |
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info:eu-repo/semantics/openAccess |
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openAccess |
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7 application/pdf |
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RCAAP |
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