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)
