置信区间计算

def solve():
    from sklearn.datasets import load_iris
    import numpy as np
    from scipy import stats
    iris = load_iris()
    data = iris.data[:, 0]
    n = len(data)
    mean = np.mean(data)
    se = np.std(data, ddof=1) / np.sqrt(n)
    t_value = stats.t.ppf(0.975, n - 1)
    ci_lower = mean - t_value * se
    ci_upper = mean + t_value * se
    print(f"样本均值: {mean:.4f}")
    print(f"标准误: {se:.4f}")
    print(f"95%置信区间: [{ci_lower:.4f}, {ci_upper:.4f}]")