Statistical Learning from a Regression Perspective (Springer Texts in Statistics)

Berk, Richard A.

ISBN 10: 3319829696 ISBN 13: 9783319829692
Published by Springer, 2018
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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.

About the Author: Richard Berk is Distinguished Professor of Statistics Emeritus from the Department of Statistics at UCLA and currently a Professor at the University of Pennsylvania in the Department of Statistics and in the Department of Criminology. He is an elected fellow of the American Statistical Association and the American Association for the Advancement of Science and has served in a professional capacity with a number of organizations such as the Committee on Applied and Theoretical Statistics for the National Research Council and the Board of Directors of the Social Science Research Council. His research has ranged across a variety of applications in the social and natural sciences.

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Title: Statistical Learning from a Regression ...
Publisher: Springer
Publication Date: 2018
Binding: Soft cover
Condition: New

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Accessible discussion of statistical learning procedures for practitioners with real-world applications in the social and policy sciencesMethods also of interest in the natural sciences and engineering Fully revised new edition with intuiti. Seller Inventory # 385706156

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Richard A. Berk
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Taschenbuch. Condition: Neu. Statistical Learning from a Regression Perspective | Richard A. Berk | Taschenbuch | xxv | Englisch | 2018 | Springer | EAN 9783319829692 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 114237694

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Seller Inventory # 9783319829692

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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 376 pp. Englisch. Seller Inventory # 9783319829692

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Taschenbuch. Condition: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 376 pp. Englisch. Seller Inventory # 9783319829692

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