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Statistical Learning from a Regression Perspective

Richard a Berk
Livre broché | Anglais | Springer Texts in Statistics
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Description

This textbook considers statistical learning applications when interest centers on the conditional distribution of the response variable, given a set of predictors, and when it is important to characterize how the predictors are related to the response.
This fully revised new edition includes important developments over the past 8 years. Consistent with modern data analytics, it emphasizes that a proper statistical learning data analysis derives from sound data collection, intelligent data management, appropriate statistical procedures, and an accessible interpretation of results. As in the first edition, a unifying theme is supervised learning that can be treated as a form of regression analysis. Key concepts and procedures are illustrated with real applications, especially those with practical implications.
The material is written for upper undergraduate level and graduate students in the social and life sciences and for researchers who want to apply statistical learning procedures to scientific and policy problems. The author uses this book in a course on modern regression for the social, behavioral, and biological sciences. All of the analyses included are done in R with code routinely provided.

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Contenu

Nombre de pages :
347
Langue:
Anglais
Collection :

Caractéristiques

EAN:
9783319829692
Date de parution :
16-06-18
Format:
Livre broché
Format numérique:
Trade paperback (VS)
Dimensions :
156 mm x 234 mm
Poids :
526 g

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