p-values for bootstrapped performance comparison

[ndiamant]

What
plots._protected_subplots makes box plots for model performance per protected class. It should also give a p-value for whether the performance across classes is the same.

Why
What we ultimately want to know is whether the performance is different across classes. You can get an idea of that from the box plots, but it's unclear what conclusion to draw from them without a p-value.

How
Figure out what p-value to calculate then make a helper function to calculate it in plots.py. Currently performance is evaluated in plots._bootstrap_performance and plots._performance_by_index.

Acceptance Criteria
plots._protected_subplots calculates and displays p-values for performance across classes being the same.

[lucidtronix]

Should we do Mann Whitney or Chi squared test here?