KNIME Statistic Nodes (Labs) version 4.3.0.v202011191636 by KNIME AG, Zurich, Switzerland
The Friedman test is used to detect any difference between subjects under test measured variously multiple times. More precisely, this non-parametric test states whether there is a significant difference in the location parameters of k statistical samples (>= 3, columns candidates, treatments, subject), measured n times (rows, blocks, participants, measures), or not. The data in each row is ranked, based on which a resulting test statistic Q is calculated.
If n > 15 or k > 4, the test statistic Q can be approximated to be Χ2 distributed. With the given significance level α, a corresponding p-value (null hypothesis H0: there is no difference of the location parameters in the samples, alternative hypothesis HA: the samples in the columns have different location parameters) can be given.
Please refer also to the Wikipedia description of the Friedman Test.
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