Langue: anglais
Edité par Routledge September 2013, 2013
ISBN 10 : 0415817099 ISBN 13 : 9780415817097
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Ajouter au panierEtat : New. Editor(s): McArdle, John J.; Ritschard, Gilbert A. Series: Quantitative Methodology Series. Num Pages: 496 pages, 117 black & white illustrations, 96 black & white tables, 59 black & white halftones, 58. BIC Classification: JHBC. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 226 x 152 x 22. Weight in Grams: 662. . 2013. 1st Edition. paperback. . . . .
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Ajouter au panierEtat : New. Editor(s): McArdle, John J.; Ritschard, Gilbert A. Series: Quantitative Methodology Series. Num Pages: 496 pages, 117 black & white illustrations, 96 black & white tables, 59 black & white halftones, 58. BIC Classification: JHBC. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 226 x 152 x 22. Weight in Grams: 662. . 2013. 1st Edition. paperback. . . . . Books ship from the US and Ireland.
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different combinations of variables in large data sets. Methodological findings and conceptual models that explain reliable EDM techniques for predicting and understanding various risk mechanisms are integrated throughout. Numerous examples illustrate the use of these techniques in practice. Contributors provide insight through hands-on experiences with their own use of EDM techniques in various settings. Readers are also introduced to the most popular EDM software programs. A related website at mephisto.unige.ch/pub/edm-book-supplement/offers color versions of the book's figures, asupplemental paper to chapter 3, and R commands for some chapters. The results of EDM analyses can be perilous - they are often taken as predictions with little regard for cross-validating the results. This carelessness can be catastrophic in terms of money lost or patients misdiagnosed. This book addresses these concerns and advocates for the development of checks and balances for EDM analyses. Both the promises and the perils of EDM are addressed. Editors McArdle and Ritschard taught the 'Exploratory Data Mining' Advanced Training Institute of the American Psychological Association (APA). All contributors are top researchers from the US and Europe. Organized into two parts--methodology and applications, the techniques covered include decision, regression, and SEM tree models, growth mixture modeling, and time based categorical sequential analysis. Some of the applications of EDM (and the corresponding data) explored include:selection to college based on risky prior academic profilesthe decline of cognitive abilities in older personsglobal perceptions of stress in adulthoodpredicting mortality from demographics and cognitive abilitiesrisk factors during pregnancy and the impact on neonatal developmentIntended as a reference for researchers, methodologists, and advanced students in the social and behavioral sciences including psychology, sociology, business, econometrics, and medicine, interested in learning to apply the latest exploratory data mining techniques. Prerequisites include a basic class in statistics. 496 pp. Englisch.
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Ajouter au panierKartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different combinations of variables in large data sets. Methodologi.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different combinations of variables in large data sets. Methodological findings and conceptual models that explain reliable EDM techniques for predicting and understanding various risk mechanisms are integrated throughout. Numerous examples illustrate the use of these techniques in practice. Contributors provide insight through hands-on experiences with their own use of EDM techniques in various settings. Readers are also introduced to the most popular EDM software programs. A related website at mephisto.unige.ch/pub/edm-book-supplement/offers color versions of the book's figures, asupplemental paper to chapter 3, and R commands for some chapters. The results of EDM analyses can be perilous - they are often taken as predictions with little regard for cross-validating the results. This carelessness can be catastrophic in terms of money lost or patients misdiagnosed. This book addresses these concerns and advocates for the development of checks and balances for EDM analyses. Both the promises and the perils of EDM are addressed. Editors McArdle and Ritschard taught the 'Exploratory Data Mining' Advanced Training Institute of the American Psychological Association (APA). All contributors are top researchers from the US and Europe. Organized into two parts--methodology and applications, the techniques covered include decision, regression, and SEM tree models, growth mixture modeling, and time based categorical sequential analysis. Some of the applications of EDM (and the corresponding data) explored include:selection to college based on risky prior academic profilesthe decline of cognitive abilities in older personsglobal perceptions of stress in adulthoodpredicting mortality from demographics and cognitive abilitiesrisk factors during pregnancy and the impact on neonatal developmentIntended as a reference for researchers, methodologists, and advanced students in the social and behavioral sciences including psychology, sociology, business, econometrics, and medicine, interested in learning to apply the latest exploratory data mining techniques. Prerequisites include a basic class in statistics.