A guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro.

An essential guide to the trouble spots and oddities of R. In spite of the quirks exposed here, R is the best computing environment for most data analysis tasks.

This is a textbook for an undergraduate course in probability and statistics. Calculus and some linear algebra knowledge is required.

This book takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required.

This tutorial manual provides a comprehensive introduction to R, an open source software package for statistical computing and graphics

This is an introduction to statistics, with R, without calculus, for students who are required to learn statistics, students with little background in mathematics and often no motivation to learn more.

This book is the perfect guide for newcomers as well as seasoned users of R who want concrete, step-by-step guidance on how to use the software easily and effectively for nearly any statistical analysis.

This book lays the foundation for further study and development in statistics using R - an ideal text for integrating the study of statistics with a powerful computational tool.

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