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Mann-Whitney U test was used for the continuous variables.
It extends the Mann-Whitney U test when there are more than two groups.
The Mann-Whitney U test was used to compare data between patients and controls.
Results were analysed using one way analysis of variance and the Mann-Whitney U test.
Results of the two groups were compared using the non-parametric Mann-Whitney U test.
The Mann-Whitney U test was then used for pairwise comparisons.
In this case the results were compared using the Mann-Whitney U Test.
Statistical analysis was performed using the Mann-Whitney U test.
The statistical significance of differences between groups was assessed by the Mann-Whitney U test.
Groups were compared with the Mann-Whitney U test.
Comparisons between the various subgroups of patients were performed using the Mann-Whitney U test.
A Mann-Whitney U test was used to assess whether women's preferences for information were influenced by various demographics.
In case of non-normal distribution the non-parametric Mann-Whitney U test was performed.
The Mann-Whitney U Test with a critical alpha level of 0.05 was used for statistical significance.
This measure was introduced by Cureton as an effect size for the Mann-Whitney U test.
Finally differences in oxygen saturation, pulse, and blood pressure between the two groups were assessed with the Mann-Whitney U test.
Statistical analysis was done with Mann-Whitney U test and Chi-square test.
Comparison of the age of different groups of cats was made using the Mann-Whitney U test.
The Mann-Whitney U test was used to evaluate the relationship between categorical demographic variables and physicians' preference values.
Statistical analysis Biochemical data were compared between groups using the Mann-Whitney U test (two-tailed).
This is supported by statistical analysis, as indicated in results of the Mann-Whitney U Test (Table 4).
A Mann-Whitney U Test verified that concentrations were greater directly downwind of the steel works.
The Mann-Whitney U test was used to assess the significance of any difference between the groups in the frequency of those with arrhythmias.
For each variable examined, the difference between men and women was tested for significance by the non-parametric Mann-Whitney U test.
The Wilcoxon rank-sum test (also known as the Mann-Whitney U test).
The Wilcoxon rank-sum test is applied to independent samples.
Further examination indicates that all the 100 genes identified by the Wilcoxon rank-sum test are included in these genes.
We used unpaired Wilcoxon rank-sum tests for the lymphoblast cell lines to test whether there is a systematic fold change across lines.
The Wilcoxon rank-sum test (also known as the Mann-Whitney U test).
The Wilcoxon rank-sum test is not the same as the Wilcoxon signed-rank test, although both are nonparametric and involve summation of ranks.
The MWW is a combination of Wilcoxon rank-sum test and Mann-Whitney U-test.
His most well-known paper contained the two new statistical tests that still bear his name, the Wilcoxon rank-sum test and the Wilcoxon signed-rank test.
Comparisons between groups for predominant symptoms were made using the Mann-Whitney U-test and Wilcoxon rank-sum test for paired comparison within patients' groups.
Subsequently, Wilcoxon rank-sum test statistics are computed in order to determine the intensity variations among conveniently chosen regions (according to the required orientation) of the samples in W.
To test for differences between the staining characteristics of MCM2 and Ki-67 both the parametric paired samples t-test and the non-parametric Wilcoxon rank-sum test were performed.
We used two-sided Wilcoxon rank-sum tests on the reported uncompared values for the two groups to test whether the expression profiles of mutant cell lines differ from those of wild-type cell lines.
Q. On what basis can you wholly discard the use of the Wilcoxon Rank-Sum Test as an alternative methodology for identifying comparable male-dominated whole groups, whereas you are not completely rejecting these other methodologies?
Q. Before you go into any further suggestions or we get clarification of those few suggestions you threw out, what about the use of the Wilcoxon Rank-Sum Test as a significance test to determine comparable male-dominated groups?
For example, for two independent samples when the data distributions are asymmetric (that is, the distributions are skewed) or the distributions have large tails, then the Wilcoxon rank-sum test (also known as the Mann-Whitney U test) can have three to four times higher power than the t-test.