I have some data which I have fitted a normal distribution to using the scipy.stats.normal objects fit function like so:
import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
import matplotlib.mlab as mlab
x = np.random.normal(size=50000)
fig, ax = plt.subplots()
nbins = 75
mu, sigma = norm.fit(x)
n, bins, patches = ax.hist(x,nbins,normed=1,facecolor = 'grey', alpha = 0.5, label='before');
y0 = mlab.normpdf(bins, mu, sigma) # Line of best fit
ax.plot(bins,y0,'k--',linewidth = 2, label='fit before')
ax.set_title('$\mu$={}, $\sigma$={}'.format(mu, sigma))
plt.show()
I would now like to extract the uncertainty/error in the fitted mu and sigma values. How can I go about this?