Kindly note that we have put a lot of effort into researching the best books on R Programming Language subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "R Programming Language" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.
1. “A First Course in Statistical Programming with R” by Braun & Murdoch
“A First Course in Statistical Programming with R” Book Review: This book provides a perfect introduction to start programming in R. It helps to adapt the source code according to our own requirements. Unlike other R introductory books, this book highlights programming, including the principles that apply to many computer languages, and the techniques used to create complex projects. The book provides numerous exercises which help to learn the language much easier. At the end of every chapter it has reviews that helps to develop confidence with the book. Solutions, data sets, and any other details is available on the book’s website. The book illustrates many examples from real applications, making it very useful for anyone working in practical data analysis.


2. “A Beginner´s Guide to R” by Zuur
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“A Beginner’s Guide to R” Book Review: This book covers everything we need to know to get started with R. To avoid the difficult level of R and statistics at the same time, this book keeps statistical methods at minimum level. This book includes how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes. The biggest advantage of the book is that it aims only to teach R, it organizes R commands in a very effective and efficient manner. This is a very simple and handy book which everyone wants to keep in their pocket or backpack all the time and easy to use.


3. “Introduction to Scientific Programming and Simulation Using R” by Chapman & Hall/CRC
“Introduction to Scientific Programming and Simulation Using R” Book Review: This book is recommended as an excellent introduction, easily readable with extensive examples and exercises. This new edition of the book presents scientific programming and stochastic modelling in a clear, effective, practical and complete manner. The book starts with basic knowledge of R and programming concepts. It discusses how to think about mathematics from a numerical point of view, including the various applications of these concepts to root finding, numerical integration, and optimisation. The new chapter on systems of ordinary differential equations, it covers topics such as Euler, midpoint, and fourthorder RungeKutta (RK4) schemes for solving systems of firstorder ODEs. It demonstrates transition and rate matrices, classification of states, limiting behaviour, Kolmogorov forward and backward equations, finite absorbing chains, and expected hitting times. It is designed for the students who want to make tools, not just use them.
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4. “R in a Nutshell” by Adler
“R in a Nutshell” Book Review: This book provides a quick, simple and practical textbook for learning R language from beginner level. It helps to learn how to write R functions and aso the use of different R packages to prepare, visualize, and analyze data. The book emphasizes each process with numerous examples from medicine, business and sports. The new edition of the book covers new and expanded chapters on R performance, the ggplot 2 data visualization package and parallel R computing with Hadoop. It illustrates how to use R to prepare for data analysis, calculate statistical fests, fit models and compute probability distributions. It also helps to speed up dynamic calculation by writing parallel R programs for Hadoop.


5. “An Introduction to R” by Venables & Smith
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“An Introduction to R” Book Review: This book provides a complete introduction to R, a software package for statistical computing and graphics. It illustrates the tutorial documentation from the R distribution, with various examples, notes and corrections.


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