scipy.stats: クラスカル・ウォリス検定 kruskal

独立標本の代表値の差の検定を行うノンパラメトリック検定である。

kruskal(*args, nan_policy='propagate', axis=0)

from scipy.stats import kruskal
import numpy as np

x = np.array([2.9, 3.0, 2.5, 2.6, 3.2])
y = np.array([3.8, 2.7, 4.0, 2.4])
z = np.array([2.8, 3.4, 3.7, 2.2, 2.0])

kruskal(x, y, z)

KruskalResult(statistic=0.7714285714285722, pvalue=0.6799647735788936)

a = np.array([41, 36, 12, 18, 28, 23, 19, 8, 7, 16, 11, 14, 18, 
        14, 34, 6, 30, 11, 1, 11, 4, 32, 23, 45, 115, 37])
b = np.array([29, 71, 39, 23, 21, 37, 20, 12, 13])
c = np.array([135, 49, 32, 64, 40, 77, 97, 97, 85, 10, 27, 7, 48, 
        35, 61, 79, 63, 16, 80, 108, 20, 52, 82, 50, 64, 59])
d = np.array([39, 9, 16, 78, 35, 66, 122, 89, 110, 44, 28, 65, 
        22, 59, 23, 31, 44, 21, 9, 45, 168, 73, 76, 118, 84, 85])
e = np.array([96, 78, 73, 91, 47, 32, 20, 23, 21, 24, 44, 21, 28, 
        9, 13, 46, 18, 13, 24, 16, 13, 23, 36, 7, 14, 30, 14, 18, 20])

kruskal(a, b, c, d, e)

KruskalResult(statistic=29.26657630611694, pvalue=6.900714118546782e-06)