R is an open-source programming language that has become the software tool of choice in statistics and data science. R has flexible data structures for organizing and storing data, graphical tools for generating statistical graphics, and sophisticated data analysis procedures for statistical inference.
Learning Base R provides an introduction to the R language for those with or without prior programming experience. It introduces the key topics that you will need to begin analyzing data and programming in R. The focus is on the R language rather than a particular methodology or application. The text contains over 400 exercises.
It is important to understand that basics of the R language (data structures, data types, functions, input/output, graphics, built-in data sets, conditional execution, looping, recursion, etc.) prior to using R packages which extend the power and capability of the language. Learning Base R surveys these fundamental aspects of the language using an example-driven approach.
More information about the book (table of contents, sample pages, videos, reviews, code) is available at www.math.wm.edu/~leemis.
Learning Base R, Second Edition