Mann-Whitney test

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Mann-Whitney test

A statistical test of the probability that two independent sets of observations come from the same population. The Mann-Whitney test is independent of distribution and can be used when the t test is inappropriate.
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Henry Berthold, U.S. mathematician, 1905–.
Mann-Whitney test - rank sum test.


Donald Ransom, U.S. statistician, 1915–.
Mann-Whitney test - see under Mann, Henry Berthold
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References in periodicals archive ?
Table 3: p values for the Mann-Whitney-Wilcoxon tests obtained for the TSC-G and C-G comparison (the statistically important values are in bold).
Concerning to the possession of household appliances (refrigerator, radio, stove and TV) or basic conditions, such as bathrooms, light, sewer and running water, the non-parametric Mann-Whitney-Wilcoxon test (MWW test) showed identical distributions (with no statistically significant differences) between the beneficiaries and non-beneficiaries, as shown in Table 1.
By running the Mann-Whitney-Wilcoxon test on the first two question data, we obtain a P-value equal to 0.369: since this value is greater than 0.05, we are not allowed to conclude that there is a statistically significant difference between the medians at the 95% confidence level.
Indeed, after one month of front lectures, students who viewed and reviewed at least two movies performed in a statistically significant way (with respect to the Mann-Whitney-Wilcoxon test) better than the other students, while taking an intermediate exam fully devoted to the visualized sorting algorithms.