#1 reduced the field of choices (IMO) to
* Matlab/Octave
* R/S+
* SAS
* Perl
* Python
* Julia
As for #2 gives preference to Python, R, Julia, Perl, or Octave (Your situation may not be as limiting).
#3 led me to many searches that all indicated that R and Python have a rich set of libraries and lots of community support.
As for #4 From Julia's website http://julialang.org/ they show nice benchmark information that indicates that Python is pretty quick.
My conclusion was that I couldn't really go wrong between R or Python. However, I chose Python because it was quicker, I like the syntax better, I like the libraries better (NumPy, SciPy, Pandas, Matplotlib) and is seems to play nicer with everything else.
This is what worked for me and how I went about deciding.
Don't sweat it -- it's only ones and zeros. -- P. Skelly