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*
These examples don't look specific to microbiome data, but the module-level doc string says that it's for power-estimation for microbiome data. Could that be generalized above?

Context on this is that people are already starting to think of scikit-bio as software for microbial ecology, but it's clearly a lot more general than that. We should try to avoid making our documentation sound microbial ecology specific for functionality that isn't.