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An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
Item #: 59936510

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

Item #: 59936510

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NZD 152

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What Stands Out

Comprehensive Coverage
Offers an extensive introduction to statistical learning techniques, integrating theoretical foundations and practical applications, making it ideal for both beginners and experienced practitioners.
R Integration
Incorporates R programming for hands-on data analysis, empowering readers to apply learned concepts directly in real-world scenarios, enhancing understanding of statistical methods.
Updated Content
The second edition includes updated examples and new applications, ensuring relevance and alignment with current trends in data science, preparing readers for contemporary challenges.

Product Details

Shop the 2nd edition of An Introduction to Statistical Learning: with Applications in R from Ubuy Cook Islands. Learn statistics and data science with this comprehensive textbook.
Publisher Springer
Publication date July 30, 2022
Edition Second Edition 2021
Language English
Print length 622 pages
ISBN-10 1071614207
ISBN-13 978-1071614204
Item Weight 7.6 ounces (215.46 grams)
Dimensions 6 x 1.25 x 9 inches (15.2 x 3.2 x 22.9 cm)
Part of series Springer Texts in Statistics

Who Should Buy?

Suitable For
  • Data Scientists

    Ideal for data scientists seeking to gain practical statistical knowledge and apply it using R programming.

  • Graduate Students

    Suitable for graduate students in statistics or related fields who need an introduction to statistical learning concepts.

  • Statistical Analysts

    Helpful for statistical analysts aiming to deepen their understanding of statistical methods and their applications in R.

Not Suitable For
  • Beginners in Statistics

    Not suitable for complete beginners, as prior knowledge in statistics and R programming is recommended.

Product Description

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)

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Intelligence & Semantics Editorial Review

An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics) is a highly acclaimed textbook published by Springer, offering a comprehensive overview of statistical learning techniques, particularly suited for aspiring data scientists. The authors, Hastie and Tibshirani, have crafted an accessible resource that balances theoretical depth and practical application, including R and Python editions. The second edition introduces new topics such as survival analysis and neural networks, vital for modern data analytics. The book is noted for its vivid figures and code examples, though some readers have mentioned a desire for more content on nonlinear regression. Overall, it serves as a strong foundation for understanding various statistical methods and their applications.

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Pros

  • Accessible to aspiring data scientists and statisticians
  • Includes R and Python editions for broader use
  • Contains new chapters on advanced statistical methods
  • Well-balanced between theory and practical application
  • Vivid figures and ample sample code enhance learning

Cons

  • Font size in print may be smaller than expected

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