As far as mathematical pre-reqs, I'll attempt to keep the math as basic as possible (interjecting proofs and more advanced things only when absolutely necessary). Having said this, if you've never seen statistics before in your life you may want to start by learning some basic statistics — you may get a bit more out of this course.
For software, we will primarily be using Python via IPython for our data analysis. Many companies and universities will use software including: R, Excel, SPSS, STATA, and so forth; we may briefly touch on some of these, but I felt that Python had the right combination of user-friendliness, power, and funcionality. Hence, some knowledge of Python will be necessary. Feel free to do the exercises given here if you need to learn Python or if you'd like a Python refresher. Also, google is your pal.
We will be using Python as the main language; specifically, we will be using Python 2.7, which is the "older" version. If you do not have Python 2.7, pick the appropriate download fiile for your operating system:
Python 2.7.5 (If you don't have it already)
As noted before, we will be using IPython; we'll download this thing called Anaconda which is a neat distribution which includes IPython and some other packages we'll need.
Get IPython via Anaconda
We'll also need to install pip for various things in future posts, but you might as well get it now.
Pip Install Instructions (Windows)
Pip Install Instructions (Not Windows)
There's a bunch of different ways to get pip; if these don't work, just google your OS and "install pip" and you should be able to find something.
To make sure Python and IPython have installed correctly, open up the Spyder program (in the ipython folder). Type in:
from numpy import * print sum(array([1,2,3,4]))
Click the green running man on top (or click "run" in the "run" menu item). If the program returns 10 in the console in the lower-right corner and doesn't give any errors, odds are that you've got it all installed correctly We will be working in Spyder for the most part, but (at least on my computer) it tends to be a bit fickle — save your work often.
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