Statistical Learning from a Regression Perspective

Author:   Richard A. Berk
Publisher:   Springer Nature Switzerland AG
Edition:   Third Edition 2020
ISBN:  

9783030401887


Pages:   433
Publication Date:   30 June 2020
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Statistical Learning from a Regression Perspective


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Author:   Richard A. Berk
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   Third Edition 2020
Weight:   0.852kg
ISBN:  

9783030401887


ISBN 10:   303040188
Pages:   433
Publication Date:   30 June 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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Reviews

It could readily be a textbook for an applications-focused course at the graduate level as each chapter comes with exercises ... . Examples with accompanying code also appear throughout the chapters which provide a scaffold for getting started ... . Berk's pragmatic advice will serve a wide audience from practitioners to educators to students. (Sara Stoudt, MAA Reviews, December 12, 2021)


“It could readily be a textbook for an applications-focused course at the graduate level as each chapter comes with exercises … . Examples with accompanying code also appear throughout the chapters which provide a scaffold for getting started … . Berk’s pragmatic advice will serve a wide audience from practitioners to educators to students.” (Sara Stoudt, MAA Reviews, December 12, 2021)


Author Information

Richard Berk is Distinguished Professor of Statistics Emeritus 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 statistical applications in the social and natural sciences.

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