Friedman Test

A Friedman Test is a non-parametric statistical test for detecting differences in treatments across multiple test attempts.

• Context:
  • It was developed by Milton Friedman in 1937.
• See: Statistical Test, Durbin Test, ANOVA, Cochran's Q Test, Kendall's W Test, Wilcoxon Signed-rank Test, Skillings–Mack Test.

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References

2016

• (Wikipedia, 2016) ⇒ http://en.wikipedia.org/wiki/Friedman_test Retrieved 2016-08-21
  • The Friedman test is a non-parametric statistical test developed by Milton Friedman. Similar to the parametric repeated measures ANOVA, it is used to detect differences in treatments across multiple test attempts. The procedure involves ranking each row (or block) together, then considering the values of ranks by columns. Applicable to complete block designs, it is thus a special case of the Durbin test.

Classic examples of use are:

• n wine judges each rate k different wines. Are any wines ranked consistently higher or lower than the others?
• n welders each use k welding torches, and the ensuing welds were rated on quality. Do any of the torches produce consistently better or worse welds?

The Friedman test is used for one-way repeated measures analysis of variance by ranks. In its use of ranks it is similar to the Kruskal–Wallis one-way analysis of variance by ranks.

Friedman test is widely supported by many statistical software packages.

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