Cover art for The Book of R, 2nd Edition
Published
No Starch, April 2025
ISBN
9781718503687
Format
Softcover, 800 pages
Dimensions
23.5cm × 17.8cm

The Book of R, 2nd Edition 2nd edition

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Due April 22, 2025.
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Produce statistical summaries, visualizations of your data, and more with the new edition of this beginner-friendly guide to R programming.

Produce statistical summaries, visualizations of your data, and more with the new edition of this beginner-friendly guide to R programming.

Even if you have no programming experience and little more than a grounding in basic math, The Book of R, 2nd Edition will teach you everything you need to know for using R effectively in 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, performing statistical tests, and modeling. You'll also learn how to create impressive data visualizations with R's graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Over 30 of hands-on exercises (with downloadable solutions) take you from theory to practice, as you explore-

The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops

Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R

How to access R's thousands of functions, libraries, and data sets

How to draw valid and useful conclusions from your data

How to create publication-quality graphics of your results

The second edition has been revised and updated from start to finish, with new content that expands the book's coverage of statistical operations, data plots, date-time-objects, and more - including dozens of fresh exercises to strengthen your skills.

Combining detailed explanations with real-world examples, The Book of R is your doorway into the wide world of data analysis.

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