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An Introduction to Statistical Learning: with Applications in R

Author(s): Gareth James1, Daniela Witten2, Trevor Hastie3, Robert Tibshirani3

1. University of Southern California 2. University of Washington 3. Stanford University

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Summary:
This book provides an introduction to statistical learning methods and is aimed for upper level undergraduate students, masters students and Ph.D. students in the non-mathematical sciences.

Licensed under these terms

Version 1.0 - published on 23 Oct 2018 doi:10.25334/Q4HT55 - cite this

Keywords

  1. linear regression
  2. textbook
  3. classification
  4. course
  5. clustering coefficient
  6. R programming language
  7. statistical learning
  8. machine learning
  9. logistic regression
  10. resampling
  11. model selection
  12. Generalized additive models
  13. decision trees
  14. principal components analysis
  15. MOOC
  16. Resources @ QUBES - Teaching & Reference

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Version Released DOI Handle Status
1.0 Oct 23, 2018 10.25334/Q4HT55 published view version »
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