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Total Size:
29.3 MB
Info Hash:
BCBE68EE5E41B17D79A479BC25ED83332E6416E7
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Added:
Nov. 14, 2025, 2:43 a.m.
Stats:
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(Last updated: Nov. 14, 2025, 2:44 a.m.)
| File | Size |
|---|---|
| Code.zip | 75.2 KB |
| Supplementary_Files.zip | 127.3 KB |
| Diamonds.zip | 362.4 KB |
| Davies T. The Book of R. A First Course in Programming and Statistics 2ed 2026.pdf | 28.7 MB |
Name
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34.3 MB
[50
/
13]
2025-12-28
| Uploaded by andryold1 | Size 34.3 MB | Health [ 50 /13 ] | Added 2025-12-28 |
NOTE
SOURCE: Davies T. The Book of R. A First Course in Programming and Statistics 2ed 2026
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COVER
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MEDIAINFO
Textbook in PDF format This long-awaited second edition folds years of updates into its beginner-friendly lessons on using R for data and statistical analysis. 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 writing programs in R. 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 tests and modeling. You’ll even learn how to create impressive data visualizations with R’s graphics tools and contributed packages, like ggplot2, ggvis, and rgl. Dozens of hands-on exercises 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 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 datasets How to draw valid and useful conclusions from your data and create publication-quality graphics of your results The Book of R brings both statistics and R to life. With clear explanations, practical examples, and hands-on exercises, this book opens the door to the evolving world of data analysis. New to this edition: The entire book has been revised and expanded, with nearly 100 pages of new content and exercises. You’ll find greater coverage of data plots and R graphics, guidance on using pipes to string together commands, and new ways to read and write external files, among many other lessons
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