Chi-square Distribution¶

In [1]:

import numpy as np
import matplotlib.pyplot as plt
import scipy.stats as stats

import numpy as np import matplotlib.pyplot as plt import scipy.stats as stats

In [2]:

headlines = ["A", "B", "C"]
headline_counts = np.array([14,8,12])
avg = sum(headline_counts) / len(headline_counts)

headlines = ["A", "B", "C"] headline_counts = np.array([14,8,12]) avg = sum(headline_counts) / len(headline_counts)

In [3]:

chi2_stat, p_value = stats.chisquare(f_obs=headline_counts, f_exp=avg)
print(f"Chi-square statistic: {chi2_stat}")
print(f"P value: {p_value}")

chi2_stat, p_value = stats.chisquare(f_obs=headline_counts, f_exp=avg) print(f"Chi-square statistic: {chi2_stat}") print(f"P value: {p_value}")

Chi-square statistic: 1.6470588235294115
P value: 0.438879929791555

In [4]:

x = np.linspace(0, 10, 100)
y = stats.chi2.pdf(x, df=2)

plt.plot(x, y)
plt.fill_between(x, y, where=(x > chi2_stat), alpha=0.5, label='P-Value')
plt.axvline(chi2_stat, color='black', linestyle='--', label='Statistic')

plt.legend()
plt.show()

x = np.linspace(0, 10, 100) y = stats.chi2.pdf(x, df=2) plt.plot(x, y) plt.fill_between(x, y, where=(x > chi2_stat), alpha=0.5, label='P-Value') plt.axvline(chi2_stat, color='black', linestyle='--', label='Statistic') plt.legend() plt.show()