The Wilcoxon Signed Rank test is a non-parametric analysis that statistically compared of the average of two dependent samples and assess for significant differences.

The Wilcoxon sign test is the non-parametric alternative of the dependent samples t-test.

**Questions Answered:**

Are test scores different from 4^{th} grade to 5^{th} grade on the same students?

Does a particular diet drug have an effect on BMI when tested one the same individuals?

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**Assumptions:**

Data comes from two matched, or dependent, populations.

The data is continuous.

Because it is a non-parametric test it does not require a special distribution of the dependent variable in the analysis.

The Wilcoxon Sign test is a repeated measures test of dependency. This test is mathematically similar to conducting a Mann-Whitney U-test (which is sometimes also called Wilcoxon 2-sample t-test). It is also similar to the basic principle of the dependent samples t-test, because just like the dependent samples t-test the Wilcoxon sign test, tests the difference of observations when the observations are matched.

However this test pools all differences, ranks them and applies a negative sign to all the ranks where the difference between the two observations is negative. This is called the signed rank.. Whereas the dependent samples t-test tests whether the average difference between two observations is 0 the Wilcoxon test tests whether the difference between two observations has a mean signed rank of 0. Thus it is much more robust against outliers and heavy tail distributions. . Thus it is the best test to compare mean scores when the dependent variable is not normally distributed.

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Related Pages:

Conduct and Interpret a Wilcoxon Sign Test