Kendall’s Rank Correlation

Tests whether two samples have a monotonic relationship.

Assumptions

• Observations in each sample are independent and identically distributed (iid).
• Observations in each sample can be ranked.

Hypothesis Formulation

• H0: the two samples are independent.
• H1: there is a dependency between the samples.

Code Implementation

# Example of the Kendall's Rank Correlation Test
from scipy.stats import kendalltau
data1 = [0.873, 2.817, 0.121, -0.945, -0.055, -1.436, 0.360, -1.478, -1.637, -1.869]
data2 = [0.353, 3.517, 0.125, -7.545, -0.555, -1.536, 3.350, -1.578, -3.537, -1.579]
stat, p = kendalltau(data1, data2)
print('stat=%.3f, p=%.3f' % (stat, p))
if p > 0.05:
	print('Probably independent')
else:
	print('Probably dependent')