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Data Analysis with R, Second Edition

You're reading from Data Analysis with R, Second Edition A comprehensive guide to manipulating, analyzing, and visualizing data in R

Product type Paperback

Published in Mar 2018

Publisher Packt

ISBN-13 9781788393720

Length 570 pages

Edition 2nd Edition

Languages

R

Tools

ggplot

Concepts

Data Analysis

Author (1):

Tony Fischetti

View More author details

Table of Contents (19) Chapters

Preface

1. RefresheR FREE CHAPTER

2. The Shape of Data

3. Describing Relationships

4. Probability

5. Using Data To Reason About The World

6. Testing Hypotheses

7. Bayesian Methods

8. The Bootstrap

9. Predicting Continuous Variables

10. Predicting Categorical Variables

11. Predicting Changes with Time

12. Sources of Data

13. Dealing with Missing Data

14. Dealing with Messy Data

15. Dealing with Large Data

16. Working with Popular R Packages

17. Reproducibility and Best Practices

18. Other Books You May Enjoy

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Using another R implementation

R is both a language and an implementation of that language. So far, when we've been talking about the R environment/platform, we've been talking about the GNU Project started by R. Ihaka and R. Gentleman at the University of Auckland in 1993, and hosted at http://www.r-project.org. Since R has no standard specification, this canonical implementation serves as R's de facto specification. If a project is able to implement this specification, and rewrite the GNU-R functionality-for-functionality and bug-for-bug-any valid R code can be run on that implementation.

Some time around 2009, various other implementations of R started to crop up. Among these were:

Renjin (running on the Java Virtual Machine)
pqR (which stands for Pretty Quick R, and written in a mix of C, R, and Fortran), FastR (which is written in Java)
Riposte (which...

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