The Elements Of Statistical Learning: Data Mining, Inference, And Prediction (Springer Series In Statistics)

The Elements Of Statistical Learning: Data Mining, Inference, And Prediction (Springer Series In Statistics)

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2003 Edition

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Frequently Asked Questions

  • Q: What is the main focus of 'The Elements of Statistical Learning'? A: 'The Elements of Statistical Learning' primarily focuses on data mining, inference, and prediction techniques in statistics, providing a comprehensive understanding of these key areas.
  • Q: Who are the authors of this book? A: The book is authored by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, all of whom are prominent figures in the field of statistics.
  • Q: What edition is available for this book? A: This listing is for the 2003 edition, which is the first printing of the 2001 edition.
  • Q: How many pages does this book contain? A: 'The Elements of Statistical Learning' contains a total of 552 pages.
  • Q: What binding does this book have? A: The book is available in hardcover binding, providing durability and a professional appearance.
  • Q: Is this book suitable for beginners in statistics? A: While the book offers valuable insights, it is generally recommended for readers with a foundational understanding of statistics and data analysis.
  • Q: What topics are covered in this book? A: The book covers a range of topics including supervised and unsupervised learning, model assessment, and various statistical methods used in data analysis.
  • Q: Can this book be used for academic purposes? A: Yes, 'The Elements of Statistical Learning' is frequently used in graduate-level courses and is considered a key resource for students and professionals in statistics and data science.
  • Q: What is the condition of the book? A: This listing describes the book as 'New', indicating it is in pristine condition and has not been previously used.
  • Q: When was this book published? A: 'The Elements of Statistical Learning' was published on January 1, 2003.