贝叶斯置信区间

def solve():
    from sklearn.datasets import load_iris
    import numpy as np
    from scipy import stats
    iris = load_iris()
    sepal_length = iris.data[:, ____]
    n = len(____)
    sample_mean = np.mean(____)
    sample_std = np.std(____)
    prior_mean = ____
    prior_std = ____
    posterior_var = ____ / (____/prior_std**____ + n/sample_std**____)
    posterior_mean = posterior_var * (____)
    posterior_std = np.sqrt(____)
    ci_lower = stats.norm.ppf(____, posterior_mean, posterior_std)
    ci_upper = stats.norm.ppf(____, posterior_mean, posterior_std)
    print(____)
    print(____)