Multiple correspondence analysis technique used in analyzing the categorical data in social sciences

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dc.contributor.authorAktürk, Duygu
dc.contributor.authorGün, Sema
dc.contributor.authorKumuk, Taner
dc.date.accessioned2025-01-27T19:00:28Z
dc.date.available2025-01-27T19:00:28Z
dc.date.issued2007
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description.abstractIt is observed that Chi-square, Fisher's Exact Probability Test, G-statistics and Z-test are frequently used in social sciences to interpret the data statistically. However, exploitation of these tests depends on some conditions. Even though these conditions are met there are still problems in interpretation of the results because the obtained data are general and limited. In this study, practical limitations of the above-mentioned tests are discussed. Then, an in-depth analysis follows on advantages and exploitation of Multiple Correspondence Analysis, which is suggested as the alternative technique that resolves the limitations of other techniques mentioned above. © 2007 Asian Network for Scientific Information.
dc.identifier.doi10.3923/jas.2007.585.588
dc.identifier.endpage588
dc.identifier.issn1812-5654
dc.identifier.issue4
dc.identifier.scopus2-s2.0-33947321464
dc.identifier.scopusqualityN/A
dc.identifier.startpage585
dc.identifier.urihttps://doi.org/10.3923/jas.2007.585.588
dc.identifier.urihttps://hdl.handle.net/20.500.12428/13338
dc.identifier.volume7
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherAsian Network for Scientific Information
dc.relation.ispartofJournal of Applied Sciences
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20250125
dc.subjectCategorical data; Correspondence analysis; Social sciences; Variable
dc.titleMultiple correspondence analysis technique used in analyzing the categorical data in social sciences
dc.typeArticle

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