Series: Chapman & Hall/CRC The R Series
426 pages, 51 b/w illustrations, 4 tables
The R Primer provides a collection of concise examples with solutions and interpretations of R problems frequently encountered by new users of this statistical software. Maintaining all the material from the first edition and adding substantial new material, the 2nd edition of The R Primer contains numerous examples that illustrate a specific situation, topic, or problem, including data importing, data management, classical statistical analyses, and high-quality graphical production. Each example is self-contained and includes R code that can be run exactly as shown, enabling results from The R Primer to be replicated.
New to the Second Edition:
- Completely revised and updated with suggestions for using new and improved R packages
- Expanded with over 100 more pages
- New solutions for covering areas from web scraping over data wrangling to waffle plots and hanging rootograms.
- Additional intermediate and advanced topics in statistical data analysis including non-parametric statistics, random forests, penalised regression and curve smoothing.
Reviews of the first edition:
"A 'primer' is supposed to be a book that covers very elementary needs. This book does so in a quite special way: It provides 142 problems with solutions, called 'rules' [...] The book efficiently addresses the many impediments against simply 'go do it' for people who have already done statistical analyses with software other than R and want to quickly learn how to do the same things in R. [...] Do I consider this book worth reading/buying ? Yes I do! [...] [it provides] a collection of useful starting points on how to accomplish practically relevant tasks for applied statistics in R."
– Ulrike Grömping, Journal of Statistical Software, January 2013
"[...] contains a number of interesting self-contained examples, each illustrating a specific situation. One of the salient features is that it covers importing data, handling data, and creating graphics. [...] Valuable for readers interested in solving statistical problems using R. Summing Up: Recommended."
– CHOICE Magazine, April 2012
"This book provides a good introduction to R, using a clear layout and detailed, reproducible examples. An ideal tool for any new R user. [...] A wide range of topics are covered, making the book suitable for a variety of readers, from undergraduate students to professionals new to R. [...] an extremely helpful introduction to a very useful statistical package."
– Claire Keeble, Journal of Applied Statistics, 2012
" [...] a nice starting point for learning R, and suitable for self-study provided the reader has some background in statistics."
– Olle Häggström, International Statistical Review, 2012
- Importing data
- Reading spreadsheets
- Importing data from other statistical software programs
- Exporting data.Manipulating data
- Working with data frames
- Transforming variables
- Statistical analyses
- Descriptive statistics
- Linear models
- Generalized linear models
- Methods for analysis of repeated measurements
- Specific methods
- Model validation
- Contingency tables
- Multivariate methods
- Resampling statistics and bootstrapping
- Robust statistics
- Non-parametric methods
- Survival analysis
- High-level plots
- More advanced graphics
- Working with graphics
- Getting information
- R packages
- The R workspace
- R Studio
- Getting information
- Using R Studio for reproducible research
- Large datasets
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Claus Thorn Ekstrøm is an associate professor of statistics in the Department of Basic Sciences and Environment and leader of the Center for Applied Bioinformatics at the University of Copenhagen. His research interests include genetic marker error detection, simulation-based inference, image analysis, and the analysis of microarray DNA chips, metabolic profiles, and quantitative traits for complex human families.