power_analysis_2.py

# power vs. number of observations 

fig = plt.figure()
ax = fig.add_subplot(2,1,1)
fig = TTestIndPower().plot_power(dep_var='nobs',
                                 nobs= np.arange(2, 200),
                                 effect_size=np.array([0.2, 0.5, 0.8]),
                                 alpha=0.01,
                                 ax=ax, title='Power of t-Test' + '\n' + r'$\alpha = 0.01$')
ax.get_legend().remove()
ax = fig.add_subplot(2,1,2)
fig = TTestIndPower().plot_power(dep_var='nobs',
                                 nobs= np.arange(2, 200),
                                 effect_size=np.array([0.2, 0.5, 0.8]),
                                 alpha=0.05,
                                 ax=ax, title=r'$\alpha = 0.05$') 
fig.subplots_adjust(top = 1.4)