confidence interval

import numpy as np
from scipy.stats import chi2

def confidence_interval_variance(data, confidence_level):
    n = len(data)
    dof = n - 1
    alpha = 1 - confidence_level

    sample_variance = np.var(data, ddof=1)
    lower_bound = (n - 1) * sample_variance / chi2.ppf(1 - alpha/2, dof)
    upper_bound = (n - 1) * sample_variance / chi2.ppf(alpha/2, dof)

    return lower_bound, upper_bound

# Пример использования
data = [2, 4, 6, 8, 10]
confidence_level = 0.95

lower, upper = confidence_interval_variance(data, confidence_level)
print(f"Доверительный интервал дисперсии: [{lower}, {upper}]")

from scipy.stats import f_oneway

def test_equal_variances(data1, data2):
    statistic, p_value = f_oneway(data1, data2)
    return statistic, p_value

# Пример использования
data1 = [2, 4, 6, 8, 10]
data2 = [1, 3, 5, 7, 9]

statistic, p_value = test_equal_variances(data1, data2)
print(f"Статистика теста: {statistic}")
print(f"p-значение: {p_value}")