This is a collection of freely available E-Books on statistics. Many of these are handy to have around in case you need a quick refresher on the underlying math of what you're trying to achieve with R. These are all written by either professional statisticians, or university level statistics professors.
Statistics - This one is a wikibook written by a number of people, but there is a PDF download available. As the title indicates, this is a first level introduction to statistics. Topics include descriptive vs. inferential statistics, distributions, statistical tests & more. For anyone new to statistics, this is a good place to start.
Introduction to Statistical Thought by Michael Lavine - This is a great first book for those interested in statistics. It differs from the other books listed in that it blends theory & application. Lavine introduces both statistics & statistical programming from the perspective of likelihood. The site makes available the data sets used in the book as well.
The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani & Jerome Friedman - This is the 10th edition of this book, and it should be the 2nd or 3rd that you read, as it goes beyond basic statistics into data mining, prediction & inference. Having said that, you definitely want this material if you're interested in R for data analysis. This book was written by 3 Stanford professors. This website also makes available the datasets & packages that are covered in the book. 764 pages.
Online Statistics Education - This is really a collection of statistics educational materials. The site offers an HTML statistics book, and this material is also available as a PDF, an e-Pub & a mobile app. These works were authored by many, and edited/compiled by David Lane. These are great resources.
Street-Fighting Mathematics by Sanjoy Mahajan - This is a textbook available for sale, but anyone can download the full book in PDF form (in the sidebar). Mahajon takes a different tack on solving math problems, he advocates laying aside rigor and getting to the solution by any means possible. He calls this opportunistic solving. While not strictly focused on statistics, this is a great read for anyone that regularly works with math.
Statistical Analysis with the General Linear Model by Jeff Miller & Patricia Haden - This book takes the reader beyond basic statistics to explain simple & multiple regression, ANOVA, ANCOVA & more. It's designed to be a textbook for a class, but it's freely available as a PDF. 274 pages.