【DA】Python 实现区间估计

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一个总体均值的置信区间

def mean_interval(mean=None, std=None, sig=None, n=None, confidence=0.95):
    """
    mean:样本均值
    std：样本标准差
    sig: 总体方差
    n:   样本量
    confidence：置信水平
    功能：构建总体均值的置信区间
    """
    alpha = 1 - confidence
    z_score = scipy.stats.norm.isf(alpha / 2)  # z分布临界值
    t_score = scipy.stats.t.isf(alpha / 2, df = (n-1) )  # t分布临界值
   
    if n >= 30 and sig != None:
        me = z_score*sig / np.sqrt(n)  # 误差
        lower_limit = mean - me
        upper_limit = mean + me
        
    if n >= 30 and sig == None:
        me = z_score*std / np.sqrt(n)
        lower_limit = mean - me
        upper_limit = mean + me
        
    if n < 30 and sig == None:
        me = t_score*std / np.sqrt(n)
        lower_limit = mean - me
        upper_limit = mean + me
    
    return (round(lower_limit, 3)