The concepts introduced and discussed in this course draw their content from various sources. Below we list the books from which most of the material comes from. For more details you are advised to check the individual lectures.
Most of the notes in the Data Analysis with R section come from my personal experience with R but everyone has its sources, influences and references.
I get most of mine directly from CRAN but some very informative links include:
Rob Kabafoff's Quick-R http://www.statmethods.net/index.html
Rob also has a very well updated book on R with the intriguing title "Awesome R in action"
A useful introduction (that somehow misses most of the fun of R) is Coursera's R-Programming Course
https://www.coursera.org/course/rprog
A very active R blog (for more advanced users) http://www.r-bloggers.com/
If you are mostly interested in the graphs, a very nice source is:
"R graphics" by Paul Murrell, which comes with a (decent) companion site containing code:
https://www.stat.auckland.ac.nz/~paul/RGraphics/rgraphics.html
Finally, a more detailed and educational (in the sense of taking things step-by-step) introduction on graphics is Winston Chang's "R graphics Cookbook" from the O'Reilly series.