Description: This textbook is a valuable resource for anyone interested in statistics or data mining. It covers a wide range of topics, including inference, prediction, and data analysis. The book is written in English and published by Springer NY as part of their Springer Series in Statistics. The authors, Trevor Hastie, Jerome Friedman, Robert Tibshirani, and J. H. Friedman, are experts in the field and provide a comprehensive overview of the subject matter. The book is available in hardcover format, with dimensions of 9.4in. x 6.5in. x 1.5in. and a weight of 51.2 Oz. It has xxii, 745 pages, making it a substantial reference for anyone looking to expand their knowledge in statistics. The book is suitable for students and professionals alike, and is a must-have for anyone interested in the subject.
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All returns accepted: ReturnsNotAccepted
Subject: Statistics
Item Length: 9.4in.
Item Height: 1.5in.
Item Width: 6.5in.
Author: Trevor Hastie, Jerome Friedman, Robert Tibshirani, J. H. Friedman
Publication Name: Elements of Statistical Learning : Data Mining, Inference, and Prediction
Format: Hardcover
Language: English
Publisher: Springer NY
Publication Year: 2017
Series: Springer Series in Statistics Ser.
Type: Textbook
Item Weight: 51.2 Oz
Number of Pages: Xxii, 745 Pages
