Includes bibliographical references and index.

Getting R and getting started -- Programming in R -- Writing reusable functions -- Summary statistics -- Creating tables and graphs -- Discrete probability distributions -- Computing normal probabilities -- Creating confidence intervals -- Performing t tests -- One-way analysis of variance -- Advanced analysis of variance -- Correlation and regression -- Multiple regression -- Logistic regression -- Chi-square tests -- Nonparametric tests -- Using R for simulation -- The "new" statistics: resampling and bootstrapping -- Making an R package -- The R Commander package.

"Beginning R: An Introduction to Statistical Programming shows you how to use this open-source language and take advantage of its extensive statistical and graphing capabilities. Indeed, R has become the de facto standard for doing, teaching, and learning computational statistics. With this book, you'll learn the language by using it right from the start--an approach giving valuable, firsthand experience"--P. [4] of cover.