Power Analysis Module

The module imperially estimates the power of a dataset using Monte Carlo simulation. The functions take test, a function which accepts a list of sample ids or values, and returns a p-value.

In conjunction with Statsmodels, the code can be used to generate power curves, for a sufficiently large number of samples. (Depending on the effect size, about 20 - 30 in each group).

I will move the statsmodel dependent example into an ipython notebook and either keep it in one of my repositories or else submit to Greg's Introduction to Applied Bioinformatics, unless statsmodel can be added.

*This code likely needs to be optimized, given the iterative nature*
What are your thoughts on splitting this function out into three public functions, one for each `mode`? Right now, it accepts a large number of parameters, many that are required for one `mode` but not another. This makes the API fairly complex (I'm having a hard time wrapping my head around this).

I think having three functions will reduce the number of parameters on each and make it clearer when one is truly required or optional. Is there a reason to join them all into a single function?