R by Example Second Edition 2024 Edition

R by Example Second Edition 2024 Edition book cover

R by Example Second Edition 2024 Edition

Author(s): Jim Albert (Author), Maria Rizzo (Author)

  • Publisher: Springer
  • Publication Date: December 10, 2024
  • Edition: Second Edition 2024
  • Language: English
  • Print length: 472 pages
  • ISBN-10: 3031760735
  • ISBN-13: 9783031760730

Book Description

Now in its second edition, R by Example Second Edition 2024 Edition is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data.

The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R.

The new edition includes expanded coverage of ggplot2 graphics, as well as new chapters on importing data and multivariate data methods.

Editorial Reviews

Review

“R by Example Second Edition 2024 Edition is a comprehensive and practical resource for individuals seeking to master data analysis and statistical computing using the R programming language. The book is designed to bridge the gap between theoretical statistical concepts and their practical application through a rich collection of examples. It caters to both beginners looking to learn R from scratch and experienced users seeking a deeper understanding of advanced statistical techniques.” (Wael Badawy, Computing Reviews, July 22, 2025)

From the Back Cover

Now in its second edition, R by Example Second Edition 2024 Edition is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data.

The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R.

The new edition includes expanded coverage of ggplot2 graphics, as well as new chapters on importing data and multivariate data methods.

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