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- from scipy import stats as st
- import numpy as np
- import math as mth
- alpha = .05 # критический уровень статистической значимости
- purchases = np.array([100, 100])
- leads = np.array([400, 500])
- p1 = purchases[0]/leads[0]
- p2 = purchases[1]/leads[1]
- p_combined = (purchases[0] + purchases[1]) / (leads[0] + leads[1])
- difference = p1 - p2
- z_value = difference / mth.sqrt(p_combined * (1 - p_combined) * (1/purchases[0] + 1/purchases[1]))
- distr = st.norm(0, 1)
- p_value = (1 - distr.cdf(abs(z_value))) * 2
- print('p-значение: ', p_value)
- if (p_value < alpha):
- print("Отвергаем нулевую гипотезу: между долями есть значимая разница")
- else:
- print("Не получилось отвергнуть нулевую гипотезу, нет оснований считать доли разными")
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