Exemplos de uso de Normality of data em Inglês e suas traduções para o Português
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Shapiro-Wilk test was used to test the normality of data.
Normality of data was evaluated with the Shapiro-Wilk test.
Shapiro-Wilk test was used for testing the normality of data.
The normality of data was determined using the Shapiro-Wilks test.
Kolmogorov-Smirnov test was used to analyse the normality of data.
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Normality of data was assessed using the Kolmogorov-Smirnov test.
We performed the Kolmogorov-Smirnov test to verify the normality of data.
The normality of data distribution was assessed by the Shapiro-Wilk test.
The ShapiroWilk test was used to assess the normality of data.
Normality of data was verified by the Kolmogorov-Smirnov test and the Q-Q graph.
In all cases it tested the normality of data by the kolmogorov-smirnov test p> 0.05.
The Kolmogorov-Smirnov test was used to verify the normality of data distribution.
At first, the normality of data was checked by means of the Shapiro-Wilk test.
The distribution of patient groups andcontrols was tested for normality of data distribution by the D'Agostino-Pearson test.
Normality of data distribution was assessed by the Shapiro-Wilk test, which revealed normal distribution.
Some commonly used statistical tests to check normality of data distribution are pointed out Fig 2.
Normality of data was verified through the Kolmogorov-Smirnov test and homogeneity of variances through the Bartlett test.
Shapiro-Wilk's test was applied to verify normality of data, which followed a normal distribution.
By the adherence test of Kolmogorov-Smirnov K-S,with the Lilliefors correction of normality, the normality of data was tested.
To compare the groups, the normality of data was initially determined using the Shapiro-Wilks test.
Regarding construct validity,we performed a preliminary analysis to ensure normality of data and suitability for factor analysis.
Normality of data was tested with the Kolmogorov-Smirnov test, which was applied to all continuous variables in each group.
For the evaluation of the distribution of the normality of data, we used the Kolmogorov-Smirnov test.
After verifying the normality of data by applying the Shapiro-Wilk W test, it was proved by the application of the Student's T-test, at a 1% significance level, that the replacement of used Class B water meters by the new Class C ones significantly reduced loss of water in the condominium; so the hypothesis of equality H0 was rejected.
The equivalence of the variances Levene Test and the normality of data Shapiro-Wilk were both verified and confirmed.
The Shapiro-Wilk test was used to test normality of data, and differences between two groups, based on continuous and symmetrical variables were tested by Student's t-test for independent samples.
Subsequently, data normality was tested by the Shapiro-Wilk test,which showed normality of data for all variables p>0.05.
Before comparing averages,we verified the normality of data and equality of variances using the Kolmogorov-Smirnov and Levene tests, respectively.
The data are shown as mean±standard deviation; the normality of data was checked using the Shapiro-Wilk test.
The Shapiro-Wilks normality test was used to verify the normality of data regarding COP and the plantar pressure distribution.