
R by Example by Jim Albert
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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A Primer of Ecology with R
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Introductory Time Series with R
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Bayesian Networks in R
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ggplot2
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A Users Guide to Network Analysis in R
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Bayesian Computation with R
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Biostatistics with R
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R For Marketing Research and Analytics
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Data Manipulation with R
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Applied Spatial Data Analysis with R
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R Coding for Ecology
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Bayesian Cost-Effectiveness Analysis with the R package BCEA
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Geostatistics for Compositional Data with R
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Modeling Dose-Response Microarray Data in Early Drug Development Experiments Using R
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Behavioral Research Data Analysis with R
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Discrete Choice Analysis with R
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Semiparametric Regression with R
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Heart Rate Variability Analysis with the R package RHRV
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Modeling Psychophysical Data in R
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Elements of Copula Modeling with R
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Modern Optimization with R
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Cultural Analytics in R: A Tidy Approach
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An Introduction to Web Mining
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Numerical Ecology with R
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Morphometrics with R
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Analysis of Integrated and Cointegrated Time Series with R
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Multistate Analysis of Life Histories with R
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Computerized Adaptive and Multistage Testing with R
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Analyzing Compositional Data with R
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Solving Differential Equations in R
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Functional and Phylogenetic Ecology in R
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Functional Data Analysis with R and MATLAB
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Mixture and Hidden Markov Models with R
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Singular Spectrum Analysis with R
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Retirement Income Recipes in R
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Quality Control with R
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Analysis of Phylogenetics and Evolution with R
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Dynamic Linear Models with R
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Applied Survival Analysis Using R
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Magnetic Resonance Brain Imaging
“R by example is a comprehensive and practical resource for individuals seeking to master data analysis and statistical computing using the R programming languageThe 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)
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).
| SKU | Unavailable |
| ISBN 13 | 9783031760730 |
| ISBN 10 | 3031760735 |
| Title | R by Example |
| Author | Jim Albert |
| Series | Use R! |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2024-12-10 |
| Number of pages | 454 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |







































