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dc.contributor.authorRoux, Brigitte Leen_US
dc.contributor.authorRouanet,Henryen_US
dc.date.accessioned2018-04-02T03:00:02Z
dc.date.available2018-04-02T03:00:02Z
dc.date.issued2010en_US
dc.identifier.isbn978-1-4129-6897-3en_US
dc.identifier.otherHPU5161265en_US
dc.identifier.urihttps://lib.hpu.edu.vn/handle/123456789/30141
dc.description.abstractRequiring no prior knowledge of correspondence analysis, this text provides a nontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte LeRoux and Henry Rouanet, present thematerial in a practical manner, keeping the needs of researchers foremost in mind.Key FeaturesReaders learn how to construct geometric spaces from relevant data, formulate questions of interest, and link statistical interpretation to geometric representations.They also learn how to perform structured data analysis and to draw inferential conclusions from MCA.The text uses real examples to help explain concepts.The authors stress the distinctive capacity of MCA to handle full-scale research studies.This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as for individual researchers.en_US
dc.format.extent126 p.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherSage Publicationsen_US
dc.subjectMultiple Correspondence Analysisen_US
dc.subjectSocial Sciencesen_US
dc.subjectQuantitative Applicationsen_US
dc.titleMultiple Correspondence Analysis (Quantitative Applications in the Social Sciences)en_US
dc.typeBooken_US
dc.size17,531 KBen_US
dc.departmentSociologyen_US


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