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Rs wilcox.test can take different length vectors, but the wilcoxon from scipy.stats cannot: I get an unequal N error message.
from scipy.stats import wilcoxon
wilcoxon(range(10), range(12))
Is there a way to get Rs behavior in Python?
990
Unlike the t-test, the Wilcoxon test doesn't assume normality, which is nice. In fact, they don't make any assumptions about what kind of distribution is involved: in statistical jargon, this makes them nonparametric tests.
Since the Wilcoxon test is a nonparametric test, the data need not be normally distributed. However, to calculate a Wilcoxon test, the samples must be dependent. Dependent samples are present, for example, when data is obtained from repeated measurements or when so-called natural pairs are involved.
The main difference is that the Mann-Whitney U-test tests two independent samples, whereas the Wilcox sign test tests two dependent samples. The Wilcoxon Sign test is a test of dependency. All dependence tests assume that the variables in the analysis can be split into independent and dependent variables.
The rank mean of one group is compared to the overall rank mean to determine a test statistic called a z-score. If the groups are evenly distributed, then the z-score will be closer to 0. In this case, the z-score is 3.81, which is equal to a p-value < 0.001.
According to the R docs:
Performs one- and two-sample Wilcoxon tests on vectors of data; the latter is also known as ‘Mann-Whitney’ test.
So just use
from scipy.stats import mannwhitneyu
mannwhitneyu(range(10), range(12))
# (50.0, 0.26494055917435472)
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