Are you interested in a general introduction, or do you have a specific goal?
1) I want to learn R because it looks fun and I will have to use some software package to get through my minor in statistics and finish my final project in neuroscience.
2) I want to learn R because I will need to use a machine learning approach to data analysis in a few months to finish my current project.
I am curious what answers show up here. I hope that the people answering the question include a little background and a brief indication of why they liked their choice.
Maybe. However, if I were to write a tutorial in R for someone interested in ANOVA (and nothing else) it might look a bit different than if they were interested in Monte Carlo methods. It also make a difference if there is an expectation to be "an expert in R" versus I can use R for some things and I am willing to work at learning other aspects of R.
So, I know a great deal about programming in SAS. That said, there are parts of the SAS software suite that I have never had to use. Even with the parts that I do use, there are options that I have not yet explored. The SAS manuals that I have run something like 15 inches of bookshelf space. I can't seem to memorize it all.
The other question is how much help is needed to program (what is an "if" statement and what does it do? Is an integer the same as a long float?) versus how much background in statistical analysis is needed?
We all must begin somewhere, but the best place to begin depends on where we want to end up. It is always possible to change direction, but that does not usually begin at the "best" place to start had we know beforehand.
I really like the book "R in action: Data analyses and graphics with R" by Robert Kabacoff, it's very basic and easy to read. Parts of the book are available via his homepage http://www.statmethods.net/ (Quick-R).