Examples of using Nonparametric variables in English and their translations into Portuguese
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Colloquial
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Medicine
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
For nonparametric variables, Fisher's exact test was used.
The Mann-Whitney U test was used to compare nonparametric variables.
Nonparametric variables are expressed as the median minimum-maximum.
Tests were performed to compare the averages of nonparametric variables with the responses related to internet usage patterns.
Nonparametric variables were summarized as median and interquartile range values.
The chi-square test was used to evaluate associations between nonparametric variables, considering a significance level≤ 0,05.
Regarding nonparametric variables, we performed a Monte Carlo correction per 1,000 patients.
Correlational analyses were performed with Pearson's test for parametric variables andSpearman's test for nonparametric variables.
For nonparametric variables, the data are presented as medians with maximum and minimum values.
Student's t tests for normally distributed variables andMann-Whitney test for nonparametric variables were used for the statistical analysis.
To nonparametric variables, Wilcoxon or Mann-Whitney tests were used, considering the mean value and interquartile range.
The different groups were compared using Student's t-tests for parametric variables andMann-Whitney tests for nonparametric variables.
For nonparametric variables, median values and interquartile ranges were calculated and Mann-Whitney test was used to compare the groups.
Parametric variables were expressed as mean± standard deviation, and nonparametric variables were expressed as median 25th-75th interquartile range.
For analyzing the nonparametric variables, the Kruscal-Wallis H test was carried out. The chi-square test was used for categorical variables. .
Mann-Whitney test andFisher's exact test were used to compare nonparametric variables and Student's t-test to compare parametric variables. .
For nonparametric variables was performed percentage and frequency distribution and to check the difference between the group Chi-square and Fisher exact test.
We used a repeated measures anova with post hoc tukey test for parametric variables, andthe friedman test with posthoc dunns for nonparametric variables.
Application of Fisher's exact test for nonparametric variables showed no statistical differences when comparing the frequencies between groups: p 0.5.
For ordinal qualitative variables, the values are presented as median and interquartile range,followed by Wilcoxon test nonparametric variables Software GraphPadPrism 6.0.
Pearson's correlation coefficient, orSpearman's coefficient for nonparametric variables, was calculated to analyze the association between two continuous variables, being adopted a 95% confidence interval.
For clinical and epidemiological characteristics,parametric variables were evaluated using the Mann-Whitney test and nonparametric variables with the likelihood ratio test.
Except for ethnicity, nonparametric variables such as smoking, alcoholism, cemented or not cemented implant, hypertension and diabetes had an impact on rates of transfusion in their analysis, with p> 0.05 Tables 1 and 3.
Continuous variables with parametric distribution were expressed as mean± standard deviation, while nonparametric variables were expressed as median and interquartile range IR.
The statistical analysis was performed with the Student's t-test or the Wilcoxon signed rank test for parametric variables andthe Mann-Whitney test for nonparametric variables.
Nonparametric variables are expressed as medians and interquartile ranges IQRs. Unpaired nonparametric variables were compared by the Wilcoxon test, whereas paired nonparametric variables were compared by the Mann-Whitney test.
To compare these variables with the outcome, Student's t-test p<0.05 was used for data with normal distribution; for nonparametric variables, the Mann-Whitney test was used p< 0.05.
Groups were compared using the Student's t-test for continuous variables, the chi-square test p< 0.05 for dichotomous variables andthe Mann-Whitney test for nonparametric variables.
Chi-square test was used for categorical variable comparisons, Pearson correlation, andLog-Rank/Mantel Cox test for nonparametric variables. p< 0,05 and CI 95% was considered as a significance.
The Kruskal-Wallis test was used toanalyze the differences between the baseline and post-stimulus values, including plasma concentrations of cortisol cosyntropin test results and other nonparametric variables.