Kindle app logo image

Download the free Kindle app and start reading Kindle books instantly on your smartphone, tablet or computer—no Kindle device required.

Read instantly on your browser with Kindle for Web.

Using your mobile phone camera, scan the code below and download the Kindle app.

QR code to download the Kindle App

Follow the authors

See all
Something went wrong. Please try your request again later.

The R Software: Fundamentals of Programming and Statistical Analysis: 40 Hardcover – 28 February 2014

4.6 out of 5 stars 3 ratings
Edition: 2013th

The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included are matrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

Product description

Review

From the book reviews:

“This is a great addition to the chorus of books on R. It is a clear an excellent resource for teaching courses on data analysis and statistical computing using R at the graduate and advanced undergraduate levels. The book can be an asset for data scientists, and even more broadly for a wide variety of users including students, teachers, researchers, software engineers, and others whose work involves statistics, mathematics, and computer science.” (Yousri El Fattah, Computing Reviews, January, 2015)

From the Back Cover

The contents of The R Software are presented so as to be both comprehensive and easy for the reader to use. Besides its application as a self-learning text, this book can support lectures on R at any level from beginner to advanced. This book can serve as a textbook on R for beginners as well as more advanced users, working on Windows, MacOs or Linux OSes. The first part of the book deals with the heart of the R language and its fundamental concepts, including data organization, import and export, various manipulations, documentation, plots, programming and maintenance. The last chapter in this part deals with oriented object programming as well as interfacing R with C/C++ or Fortran, and contains a section on debugging techniques. This is followed by the second part of the book, which provides detailed explanations on how to perform many standard statistical analyses, mainly in the Biostatistics field. Topics from mathematical and statistical settings that are included arematrix operations, integration, optimization, descriptive statistics, simulations, confidence intervals and hypothesis testing, simple and multiple linear regression, and analysis of variance. Each statistical chapter in the second part relies on one or more real biomedical data sets, kindly made available by the Bordeaux School of Public Health (Institut de Santé Publique, d'Épidémiologie et de Développement - ISPED) and described at the beginning of the book. Each chapter ends with an assessment section: memorandum of most important terms, followed by a section of theoretical exercises (to be done on paper), which can be used as questions for a test. Moreover, worksheets enable the reader to check his new abilities in R. Solutions to all exercises and worksheets are included in this book.

Product details

  • Publisher ‏ : ‎ Springer
  • Publication date ‏ : ‎ 28 February 2014
  • Edition ‏ : ‎ 2013th
  • Language ‏ : ‎ English
  • Print length ‏ : ‎ 665 pages
  • ISBN-10 ‏ : ‎ 1461490197
  • ISBN-13 ‏ : ‎ 978-1461490197
  • Item weight ‏ : ‎ 1.25 kg
  • Dimensions ‏ : ‎ 15.75 x 3.05 x 23.88 cm
  • Part of series ‏ : ‎ Statistics and Computing
  • Customer Reviews:
    4.6 out of 5 stars 3 ratings

About the authors

Follow authors to get new release updates, plus improved recommendations.

Customer reviews

4.6 out of 5 stars
3 global ratings

Review this product

Share your thoughts with other customers

Top reviews from Australia

There are 0 reviews and 0 ratings from Australia

Top reviews from other countries

  • Peter
    5.0 out of 5 stars Five Stars
    Reviewed in the United States on 18 February 2017
    Format: HardcoverVerified Purchase
    Excellent book. One of the best on R.
  • Bill Cunningham
    5.0 out of 5 stars Five Stars
    Reviewed in the United States on 13 April 2015
    Format: HardcoverVerified Purchase
    Great addition to forensic and grant work library