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dc.contributor.authorDiday, Edwin
dc.contributor.authorBillard, Lynne
dc.subjectBasic descriptive statisticsen
dc.subjectmulti-valued variablesen
dc.subjectinterval-valied variablesen
dc.subjectsymbolic sample mean an symbolic sample varianceen
dc.subjectmodal-valued random variablesen
dc.subjectvirtual hospital histogramsen
dc.subjectsymbolic data and so-called rulesen
dc.titleSymbolic Data Analysis : Conceptual statistics and data Miningen
dc.typeChapitre d'ouvrage
dc.contributor.editoruniversityotherUniversity of Georgia;États-Unis
dc.description.abstractenThe first book to present a unified account of symbolic data analysis methods in a consistent statistical framework, Symbolic Data Analysis features a substantial number of examples from a range of application areas, including health, the social sciences, economics, and computer science. It includes implementation of the methods described using SODAS software, which has been developed by a team led by Edwin Diday and is freely available on the Web, with an additional chapter that provides a basic guide to the software. It also features exercises at the end of each chapter to help the reader develop their understanding of the methodology, and to enable use of the book as a course text. The book is supported by a website featuring a link to download SODAS software, datasets, solutions to exercises, and additional teaching material.en
dc.relation.ispartofseriestitleWiley Series in Computational Statisticsen_US
dc.relation.ispartoftitleSymbolic Data Analysisen
dc.relation.ispartofeditorDiday E. ; Billard L.
dc.relation.ispartofpublnameWiley Interscienceen
dc.relation.ispartofpublcityChichester (England) Hoboken (NJ)en
dc.subject.ddclabelProbabilités et mathématiques appliquéesen

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