#### Import

import scipy.stats as stat

#### Regression

stat.linregress(x, y) -> (slope, intercept, r, p-value, standard_error)

xs = np.array([min(x), max(x)])

p.plot(xs, reg_out[1] + xs * reg_out[0])

#### T-tests

##### One sample against a theoretical mean

t, pval = stat.ttest_1samp(x, mean) ->

##### Two samples against each other

t_2samp, p_2samp = stat.ttest_ind(x, y)