Exemplos de uso de Assumption of normality em Inglês e suas traduções para o Português
{-}
-
Colloquial
-
Official
-
Medicine
-
Financial
-
Ecclesiastic
-
Ecclesiastic
-
Computer
-
Official/political
Thus, the assumption of normality was fulfilled.
The Shapiro-Wilk's test of normality was performed to verify the assumption of normality.
As the assumption of normality was not met, the data are shown as median Md and its quartiles 1st-3rd.
The non-parametric Wilcoxon test was used to compare the two techniques, because the assumption of normality of the data was rejected.
To test the assumption of normality of the variables involved in the study, Shapiro-Wilk test was applied.
The univariate analysis andquantitative characteristics were done with test F ANOVA when the assumption of normality was satisfied and Kruskal-Wallis, on the contrary.
Not satisfied the assumption of normality and homoscedasticity by Shapiro-Wilk and Levene's tests, the Kruskal-Wallis test was performed.
In this work we develop an extension of theclassic factor analysis model, by relaxing the assumption of normality of the factors.
The Kolmogorov-Smirnov test was used to assess the assumption of normality of the retinol serum variable, described as mean and standard deviation.
Comparative analyses were then performed, applying the Student t test for paired data orthe Wilcoxon test for variables that did not meet the assumption of normality.
The principal components analysis wasthe factor extraction method, its advantage being that there is no assumption of normality of the variables involved, which is appropriate for the Likert scale used in our study.
Subgroup comparison was performed with an unpaired t-test for continuous variables with normal distribution orwith the Wilcoxon rank-sum test when the assumption of normality was not met.
Using a QQ plot of the mean scores, the assumption of normality of scores was confirmed, that is, as the points are close to the line, the t-test can be used to compare the means of the data, as shown in Table 3 and Fig.
Variables age, sway velocity andellipsis area were transformed by means of a logarithmic function because assumption of normality was rejected by the Kolmogorov-Smirnov test.
The most common violation is the assumption of normality of error terms, 9 which means that the differences between the estimated model and the data observed are not frequently zero or close to zero anymore, i.e.
The estimation method used was that of maximum likelihood, which allows one to obtain better results,even with the violation of the assumption of normality Marôco, 2010; Kline, 2010.
For cases in which the assumption of normality was not met, the quantitative variables were expressed as median, first quartile Q1, third quartile Q3, minimum and maximum values, and the comparison between groups was performed using the Mann-Whitney test.
The non-parametric test of Mann-Whitney U was used to compare participants with and without osteoarthritis andquantitative variables, since the assumption of normality was not accepted Kolmogorov-Smirnov.
The most common violation is the assumption of normality of error terms, which means that the differences between the estimated model and the data observed are not frequently zero or close to zero anymore, i.e. that the differences above zero do not only occur occasionally.
The qualitative variables were described by absolute frequency n and relative%; and quantitative through descriptive measures minimum, maximum, average andstandard deviation when satisfy the assumption of normality.
Although the assumption of normality of the residuals is not a requirement for logistic regression, the continuous variableswere natural-log transformed to achieve a normal distributionin an effort to mitigate possible"scale effects" in the regressions. As shown in Table 4, after transformation, only the UPSTREAM variable remained non-normally distributed.
The total WAI score had a normal distribution both in the test p 0.587 and retest p 0.237,enabling the performance of analyses that took into consideration the assumption of normality, such as Bland-Altman plot.
In the statistical analysis, to compare the means of the scores obtained by the above groups, the Wilcoxon nonparametric test was used,since this would not need the assumption of normality of the score measurements.
The groups of patients were compared as to quantitative variables by using variance analysis for data with normal distribution;Kruskal-Wallis test was used for data whenever the assumption of normality was not met.
The qualitative variables were expressed as frequency percentage, and the quantitative variables were analyzed with the Kolmogorov-Smirnov test to determine the type of distribution;those which met the assumption of normality were presented as mean and standard deviation.
In univariate analysis, the comparison among pregnant women with and without UI was conducted with a chi-square test for the categorical variables, a t-test for independent samples for the quantitative variables with normal distribution anda Mann-Whitney test when assumption of normality was not considered.
The following statistical tests were used: 1 Student's t-test, for the comparison between groups, 2 Kolmogorov-Smirnov test to verify the validity of the normality assumption, and 3 Wilcoxon andMann-Whitney tests, when the assumption of normality was not valid.
For the quantitative variables birth weight, corrected gestational age, chronological age in days, length of hospitalization in days, Apgar 1' and 5', cephalic perimeter, thoracic perimeter, number of punctures, Student's t test or Non-parametric test of Mann-Whitney was used,when the assumption of normality could not be verified.
For comparison of the means of quantitative variables birth weight, corrected GA, CA in days, length of stay in days, 1' and 5' Apgar, HC, CC, number of punctures with the PIPP pain scores pain and no pain, the Student's t-test ornonparametric Mann-Whitney test were used when the assumption of normality test could not be found.
The assumptions of normality were assessed using the Kolmogorov-Smirnov test.