File:Binomial confidence band uk.svg
Summary
| Description |
English: Illustration of confidence bands using simulated data, labelled in Ukrainian
Українська: Ілюстрація довірчих смуг із застосуванням імітованих даних |
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| SVG development | Category:Valid SVG created with Matplotlib code#Binomial%20confidence%20band%20uk.svg  The file size of this SVG plot may be irrationally large because its text has been converted to paths inhibiting translations. |
| Source code | Python codeimport numpy as np
import matplotlib.pyplot as plt
import scipy.special as sp
X = np.arange(18, 81, 2)
P = 1/(1+np.exp(1-0.2*np.sqrt(X-18)))
Y,S,n = [],[],500
for i,x in enumerate(X):
y = 1*(np.random.uniform(size=n)<P[i])
p = y.mean()
Y.append(p)
S.append(np.sqrt(p*(1-p)/n))
Y = np.array(Y)
S = np.array(S)
## Множник для одночасно 95 %-вої довірчої смуги із застосуванням методу Бонферроні.
f = -sp.ndtri(0.025/len(P))
plt.clf()
plt.plot(X, Y, '-', color='black', label = 'Оцінка')
plt.plot(X, Y+2*S, '-', color='royalblue', label = 'Поточково 95 %-ва ДС')
plt.plot(X, Y-2*S, '-', color='royalblue')
plt.plot(X, Y+f*S, '-', color='orangered', label = 'Одночасно 95 %-ва ДС')
plt.plot(X, Y-f*S, '-', color='orangered')
plt.plot(X, P, '-', color='green', label = "Істинні частки")
plt.ylim(0,1)
plt.xlim(18,80)
plt.legend(frameon=False)
plt.xlabel("Вік")
plt.ylabel("Частка тих, хто підтримує кандидата А")
plt.savefig("binomial_confidence_band_uk.png")
plt.savefig("binomial_confidence_band_uk.svg")
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