Best is meaningless without a measure of goodness. (from Optimization) You are going to get a slew of candidate bests but folks aren't going to often articulate what makes it best. there will conflicting or even mutually exclusive rubrics.
The goal of the language might include:
- inexpensive (starving college student budget)
- employable (typically used and valued in your post degree career)
- fast enough (not every grad student needs to run on a supercomputer to get their job done)
- great breadth and depth of libraries
IMO the "R" language does some of these really well.
- It imports into JMP, SAS, and Python so you can wrapper it for your job.
- It is engineered and maintained by stats/math grad students so it is wide, deep, and mostly correct
- It is open source so it is free
Personally I use MatLab, which was taught in school and it hurts for the following reason:
- where I work is JMP-dominant, so it is pulling teeth to stay in the $5k/yr CAL.
- nobody else here speaks the language (statistically speaking) so I have to do extensive hand-holding to share the code
- If I am not connected by VPN to the work CAL server, I can't turn on my software
As long as I am not doing CFD I find the interpreted language is good enough. Computers today are much better than the supercomputers of 15 years ago. We have smart-phones with better CPU's than a bleeding edge Pentium II yesteryear.
I particularly like RStudio as an IDE.