As an aspiring R-learner, I have a few quibbles in the first pages I've looked at:

re: the Assignment operator http://www.studytrails.com/R/Core/AssignmentOperator.jsp

> However, there is a difference between the two operators. = is only allowed at the top level i.e. if the complete expression is written at the prompt. so = is not allowed in control structures. Here's an example:

> if (aa=0) {print ("test")}
Error: unexpected '=' in "if (aa="
> aa
Error: object 'aa' not found
> if (bb<-0) {print ("test")}
> bb
[1] 0

What in the LOLWTF...This is a bad example because even as an experienced programmer, I have no idea what is supposed to happen, or why this pattern would even be used -- and even then, I was surprised with the result. This is an overly complicated explanation even if it is correct. I prefer Hadley Wickham's style guide:

http://adv-r.had.co.nz/Style.html

> Use <-, not =, for assignment.

(an assignment operator that isn't an equals sign is one of the things I miss most when switching away from R)

From the next chapter, Listing Objects: http://www.studytrails.com/R/Core/ListingObjects.jsp

> All entities in R are called objects. They can be arrays, numbers, strings, functions.

This may technically be the case, but any R tutorial that does not open up with what makes R different from other mainstream languages is doing the reader a major disservice. This Listing Objects chapters shows patterns that use R in ways that I haven't seen used in other R examples (beginner and advanced). Even if it's correct, what's the point in showing esoteric examples unless this tutorial is meant to teach R to someone interested in the design of languages?

Again, Wickham's Advanced R book handles this topic well (in fact, Advanced R is probably the best book you can read if you already know how to program -- it is incredibly accessible) in his early chapter on Data structures:
http://adv-r.had.co.nz/Data-structures.html

> R’s base data structures can be organised by their dimensionality (1d, 2d, or nd) and whether they’re homogeneous (all contents must be of the same type) or heterogeneous (the contents can be of different types). This gives rise to the five data types most often used in data analysis...Almost all other objects are built upon these foundations. In the OO field guide you’ll see how more complicated objects are built of these simple pieces.

And this next sentence is the one thing I wished someone had printed out and stapled to my forehead before I started to learn R:

> Note that R has no 0-dimensional, or scalar types. Individual numbers or strings, which you might think would be scalars, are actually vectors of length one.

Maybe that's self-evident to other programmers, but even as someone who once programmed in MATLAB, I was stunningly ignorant I was of how every return value I interacted with was a vector, even a single simple string. In retrospect, the interactive shell alludes to this...but I didn't even bother looking up the details about the shell:

> 2 + 2
[1] 4
> 'a'
[1] "a"

R is wonderfully easy to start up with and produce visualizations with. But skipping over the language's fundamentals was incredibly painful for me. A few minutes skimming "Advanced R" would have easily saved me hours of confusion.