用scipy求置信区间confident interval和随机生成分布样本

from scipy import stats
import numpy as np
import math

s = np.array([1, 2, 3, 4, 4, 4, 5, 5, 5, 5, 4, 4, 4, 6, 7, 8])
n, min_max, mean, var, skew, kurt = stats.describe(s)
std = math.sqrt(var)
# std为标准差, 如需求方差s.std() and s.var()
# loc为mean, scale为标准差.
# 求正态分布95%置信区间
CI = stats.norm.interval(0.95, loc=mean, scale=std)
# 随机生成1000个样本
norm_samples = stats.norm.rvs(loc=mean, scale=std, size=1000)
# 求gamma置信区间 gamma(a, b)
CI_gamma = stats.gamma.interval(0.95, a, scale=1/b)
# 随机生成1000个样本
gamma_samples = stats.gamma.rvs(a, scale=1/b, size=1000)