Examples of using Groups were compared in English and their translations into Portuguese
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
The groups were compared by using the non-parametric Mann-Whitney U test for continuous variables,
The means of groups were compared by means of an analysis of variance one criterion α 0.05.
The categorical variables were analyzed by means of percentage frequencies, and the groups were compared by means of the Chi-Squared and Fisher's Exact Tests.
The groups were compared using chi-square Pearson chi-square for categorical variables
Groups were compared using Student's t-tests
Differences between the groups were compared with T-tests, with p-values corrected for multiple comparisons by the Bonferonni procedure.
The groups were compared by means of the Student's t-test and ANOVA for continuous independent variables,
Regarding qualitative variables, the groups were compared by using Fisher exact test
Groups were compared using one-way analysis of variance ANOVA followed by Bonferroni's multiple comparison test.
The differences in proportions between the groups were compared using a chi-square
of scores and groups were compared using the mann-whitney test.
Differences in continuous variables between groups were compared by t test
Differences in continuous variables between groups were compared using the unpaired t-test when the variable had a normal distribution
The groups were compared with regard to age by using variance analysis with a fixed factor.
Therefore, the differences between groups were compared using the Mann-Whitney test
body surface area of both groups were compared by the Student t test.
BBS, SOT, RWS, LOS scores of groups were compared using the independent t test.
Once detected a rejection of the hypothesis of equality, the groups were compared two by two by the same test.
differences in the prevalence between groups were compared via chi-square analyses.
The clinical differences obtained through digital-photographical analysis for both groups were not statistically significant when both groups were compared p.