Synopses & Reviews
Newcomers to R are often intimidated by the command-line interface, the vast number of functions and packages, or the processes of importing data and performing a simple statistical analysis. The R Primer provides a collection of concise examples and solutions to R problems frequently encountered by new users of this statistical software.
Rather than explore the many options available for every command as well as the ever-increasing number of packages, the book focuses on the basics of data preparation and analysis and gives examples that can be used as a starting point. The numerous examples illustrate a specific situation, topic, or problem, including data importing, data management, classical statistical analyses, and high-quality graphics production. Each example is self-contained and includes R code that can be run exactly as shown, enabling results from the book to be replicated. While base R is used throughout, other functions or packages are listed if they cover or extend the functionality.
After working through the examples found in this text, new users of R will be able to better handle data analysis and graphics applications in R. Additional topics and R code are available from the book 's supporting website at www.statistics.life.ku.dk/primer/
Synopsis
An ideal introduction for readers from all disciplines, this book provides examples and solutions (including code) to technical problems that are commonly encountered by beginners and intermediate users of the R statistical programming package. Unlike most existing texts, this one is not meant to teach statistics; rather, it shows readers how they can perform various tasks using the R program. The author explores problems with importing data, transforming data, making statistical analyses, creating graphics for scientific publications, and installing R packages.