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The Book of R: A First Course in Programming and Statistics

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"The Book of R" is a comprehensive, beginner-friendly guide to R, the world's most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you'll find everything you need to begin using R effectively for statistical analysis.

You'll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You'll even learn how to create impressive data visualizations with R's basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package.

Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loopsStatistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in RHow to access R's thousands of functions, libraries, and data setsHow to draw valid and useful conclusions from your dataHow to create publication-quality graphics of your resultsCombining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R's functionality. Make "The Book of R" your doorway into the growing world of data analysis.

792 pages, Paperback

First published November 25, 2015

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Displaying 1 - 7 of 7 reviews
Profile Image for Mikhael Hayes.
110 reviews
April 25, 2025
So glad to be done with this. It does the job, but it makes me feel like it's 2008 and I'm learning to type or something
Profile Image for Mike Harris.
236 reviews4 followers
July 15, 2019
This book has one of better over views of R and statistical modeling for people new to R and statistical modeling. Maybe if I did not read it cover to cover and just read the middle part I would have given it a 4 but I felt that the last section on graphs just dragged on.

I did almost all of the exercises and found them to be okay for re-enforcing the content.

The diamond data 404s now but if you use the diamond data set that comes with ggplot2 you’ll be able to follow along with the examples and do the exercises which use the diamond data set.
Profile Image for Jaime.
4 reviews
March 25, 2020
A great approach to learning R and how to implement it into a working environment of Data Analysis and database management.
Profile Image for Nathaniel Inman.
42 reviews2 followers
July 28, 2022
It's rare to see an author that not only covers a language breadth but also isn't afraid to reach depths in practical applications. This book is tailored towards a computer or data scientist, although the layperson with a good foundation in discrete math, calculus and statistics will feel comfortable. The first third covers the language itself, slowly introducing language semantics and common patterns before sliding into statistical analysis such as p values, linear regression, etc. If I had to nitpick, from an engineering perspective I would have enjoyed digging into the S4 structure. My page tabs are on 48, 84, 97, 130, 171, 176, 207, 227, 242, 251, 274, 278, 298, 326, 369, 378, 387, 391, 405, 460 & 463.
Profile Image for Christopher Hall.
69 reviews1 follower
December 29, 2017
Excellent book. This took me from no knowledge of R and relatively little knowledge of programming to being conversant in R. And I got a job offer partly as a result of my skills in R!

The book covers the basic aspects of programming all the way to introducing complex statistical concepts and creating full-color 3D plots. Each section (about 4 per chapter) has exercises to practice the concepts covered.

I know I'll be using this a reference for years to come.
Displaying 1 - 7 of 7 reviews

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