Examples of using Distributed continuous 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
Normally distributed continuous variables were analyzed by unpaired t-test.
One-Factor Analysis of Variance ANOVA was used to assess the groups with normally distributed continuous variables.
Non-normally distributed continuous variables were analyzed using Mann Whitney U test.
The statistical analysis used Student's t test to compare two groups of normally distributed continuous variables, and the Mann-Whitney test was used for non-normal distributions.
Asymmetrically distributed continuous variables were expressed as medians and interquartile ranges.
Both groups were compared using chi-square test or Fisher's exact test for qualitative variables when appropriate, andindependent t-test for normally distributed continuous variables.
Normally distributed continuous variables were compared using unpaired student t-test, and categorical variables were compared using the chi-squared test.
In comparing two independent groups, the Student's t-test was used if the continuous variables were normally distributed, andthe Mann-Whitney U test was used for non-normally distributed continuous variables.
Normally distributed continuous variables are expressed as mean± standard deviation SD, and skewed distributions are presented as median IQR25-75.
Statistical analysis- Data are presented as mean andstandard deviation parametrically distributed continuous variables, median nonparametrically distributed continuous variables, and percentage categorical variables.
Normally distributed continuous variables were compared by the unpaired Student t test and one-way analysis of variance with the Bonferroni test for multiple comparisons.
Comparisons between groups were performed with the chi-square test for dichotomous variables,Student's t-test for normally distributed continuous variables, and the Mann-Whitney U-test for non-normally distributed continuous variables.
Normally distributed continuous variables were compared using the Student t test, and, for those non normally distributed, the Kruskal-Wallis test was used to assess differences between variables.
The Student's t-test was used to compare symmetrically distributed continuous variables between groups and the Mann-Whitney test, for asymmetric distributions.
Normally distributed continuous variables are presented as means and were evaluated by Student'st test, whereas variables that were not normally distributed were evaluated by Mann-Whitney's test and are presented as medians.
The measures of central tendency and dispersion are expressed as means andstandard deviation mean± SD for symmetrically distributed, continuous variables, and as median, minimum and maximum values for the ones with asymmetric distribution.
For multivariate analysis of not normally distributed continuous variables, logarithmic transformation was carried out, followed by multiple linear regression analysis with the aforementioned inclusion criteria.
Patients were categorized into two as poor Group I or good Group II BDI score. Comparisons between groups of patients were made by use of a?2 test for categorical variables,independent samples t test for normally distributed continuous variables, and Mann-Whitney U test when the distribution was skewed.
Normally distributed continuous variables were described as mean± standard deviation SD, non-normally distributed continuous variables were described as median and interquartile range and categorical variables were described as numbers and/or percentages.
Continuous normally distributed variables determined by Kolmogorov-Smirnov test were compared using ANOVA and reported as means standard error.
The paired Student"t" test for paired and non-paired values, as indicated,was used when variables were normally distributed and continuous.