LaTeX for students

Distributions (what to install):

A version of LaTeX can be installed for free on your computer no matter what kind of computer/OS you have:

1. MikTeX (for Windows): http://miktex.org
2. MacTeX (for Mac): http://www.tug.org/mactex/
3. TeXLive (for Linux, BSD, etc.): install the version of LaTeX available through your package manager.

Mathematica/Maple/Matlab

The "Three M's" of commercial Mathematics software. Mathematica and Maple are "Computer Algebra Systems" (CAS) with an emphasis on symbolic computing, while Matlab is a numerical computing based system. GW has a site license for Mathematica which allows all GW students free installs (see here). Maple and Matlab are available in campus computer labs. All of the above (and most below) have excellent graphical capabilities.

There are various free alternative software packages that can replace the rather expensive software dicaussed above: Instead of Mathamatica or Maple, consider using wxMaxima (GUI for open source version of Maxima, one of the earliest CAS. Not as fully featured as its commercial cousins, but decent). Or try the huge Sage (based on Maxima, Python and many other packages). Two decent free Matlab alternatives are GNU Octave or Scilab.

For any work involving statistics or data you would do well to consider R. It can also do a lot of what Matlab can do.

Also, Python together with some of its packages (NumPy, SciPy, Mathplotlib, SymPy) can do a lot of what all of the above can do.  Sage (see above) contains a full implementation of Python with all of the mentioned packages installed, but you might also consider a distribution like Anaconda, which is just Python together with a selection of packages for technical computing.

Added 8/2018. I recently used Julia to do some significant computations, and would recommend trying it. Like Matlab, it is primarily numerical computing platform, designed with higher level mathematics in mind. It was specifically designed to be fast. Code is compiled (on the fly) rather than interpreted. It is easy to learn: its programming style is somewhat like Python. Julia can run inside a jupyter notebook, which is nice (a lot like Mathematica or Maple). But unfortunately, Julia does lack its own graphics package, so one needs to borrow a graphics package from elsewhere. I used PyPlot (borrowed from Anaconda Python), which was easier to install in Windows than in Mac OS X (go figure). Also, I found the pictures a little crude compared to Mathematica, Maple or Matlab.