Overview
- Introduces the R system, their capabilities required to perform basic numerical and graphical summaries of data
- Introduces using R for simulation including Monte Carlo experiments and Bayesian computation
- Features a new chapter on data frames, as well as new coverage on data mining, Rstudio, knitr, and dplyr
Part of the book series: Use R! (USE R)
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About this book
Now in its second edition, R by Example is an example-based introduction to the statistical computing environment that does not assume any previous familiarity with R or other software packages. R functions are presented in the context of interesting applications with real data.
The purpose of this book is to illustrate a range of statistical and probability computations using R for people who are learning, teaching, or using statistics. Specifically, it is written for users who have covered at least the equivalent of (or are currently studying) undergraduate level calculus-based courses in statistics. These users are learning or applying exploratory and inferential methods for analyzing data, and this book is intended to be a useful resource for learning how to implement these procedures in R.
The new edition includes expanded coverage of ggplot2 graphics, as well as new chapters on importing data and multivariate data methods.
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Table of contents (15 chapters)
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Front Matter
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Back Matter
Reviews
“R by example is a comprehensive and practical resource for individuals seeking to master data analysis and statistical computing using the R programming language. The book is designed to bridge the gap between theoretical statistical concepts and their practical application through a rich collection of examples. It caters to both beginners looking to learn R from scratch and experienced users seeking a deeper understanding of advanced statistical techniques.” (Wael Badawy, Computing Reviews, July 22, 2025)
Authors and Affiliations
About the authors
Maria Rizzo is professor of statistics at Bowling Green State University. Her recent book publications include Statistical Computing with R, 2e (2019) and Energy Statistics (forthcoming).
Jim Albert is professor of mathematics and statistics at Bowling Green State University. His recent book publications include Analyzing Baseball Data with R, 2e (with Max Marchi and Benjamin S. Baumer, 2018), Visualizing Baseball (2017), and Bayesian Computation with R (Springer 2009).
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Bibliographic Information
Book Title: R by Example
Authors: Jim Albert, Maria Rizzo
Series Title: Use R!
DOI: https://doi.org/10.1007/978-3-031-76074-7
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024
Softcover ISBN: 978-3-031-76073-0Published: 10 December 2024
eBook ISBN: 978-3-031-76074-7Published: 09 December 2024
Series ISSN: 2197-5736
Series E-ISSN: 2197-5744
Edition Number: 2
Number of Pages: XV, 454
Topics: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Statistics and Computing/Statistics Programs, Probability and Statistics in Computer Science, Statistical Theory and Methods, Coding and Information Theory