Exemplos de uso de Homogeneity of variances em Inglês e suas traduções para o Português
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The homogeneity of variances among groups was assessed by the Levene test.
For statistical analysis,data was tested for normality and homogeneity of variances.
The homogeneity of variances between the groups was assessed by use of the Bartlett's test.
The premises of Variance Analysis are the normality and homogeneity of variances.
Homogeneity of variances of numerical variables was observed using the Bartlett test.
The Kolmogorov-Smirnov andLevene tests were used to check the normality and homogeneity of variances respectively.
The groups showed homogeneity of variances, both daily intervention and globally.
Normality of data was verified through the Kolmogorov-Smirnov test and homogeneity of variances through the Bartlett test.
The homogeneity of variances was calculated with the Levene test and the Lilliefors significance correction test.
The Shapiro-Wilk and Levene tests were used to verify the pre-concepts of normality and homogeneity of variances, respectively.
Homogeneity of variances was calculated using Levene's test and Lilliefors significance correction.
For the performance of Student's t-test and ANOVA,Levene's test was also used to examine the homogeneity of variances.
When homogeneity of variances was not verified, adjustment was performed with the Brown-Forsythe(BF) test.
Data normality was initially tested using the Kolmogorov-Smirnov test, and the homogeneity of variances was tested by the Levene's test.
The test of homogeneity of variances was applied to evaluate the normal distribution of the studied variables.
Continuous variables were tested for normal distribution with the Kolmogorov-Smirnov test and homogeneity of variances by the Levene test.
Data normality and homogeneity of variances were verified by Kolmogorov-Smirnov and Levene tests, respectively.
Next, we used the Shapiro-Wilks test to check the distribution of variables andthe Levene test to check homogeneity of variances.
It was verified the homogeneity of variances for each variable and the normality of the data was verified using Shapiro-Wilk test.
The results were evaluated according to the parametric assumptions of normality Lilliefors test and homogeneity of variances Levene test.
For quantitative variables, the homogeneity of variances was determined by the Lavene test and the normality by the Kolmogorov-Smirnov test.
Numerical variables were submitted to the Komolgorov-Smirnov and Levene tests to verify, respectively,the normal distribution and homogeneity of variances.
The assumptions of normal distribution in each group and homogeneity of variances among the groups were evaluated by the Shapiro-Wilk test and the Levene test, respectively.
The evaluation of the normal distribution was performed using the Kolmogorov-Smirnov test and Levene's test for homogeneity of variances.
In assessing the homogeneity of variances Levene's test and the effect size, it was possible to observe in AV1 P 0.144 and 0.48, AV2 P 0.001 and 0.23, AV3 P 0.675 and 0.68, and AV4 P 0.068 and 0.75, respectively.
Data on RF and Nematodes•g were tested for normality by Shapiro-Wilk test and homogeneity of variances by Hartley test, at 5% probability.
Data were normal distribution analysis of waste and homogeneity of variances and later submitted to t test and mann-whitney test for nonparametric variables, the level of 5% error probability.
Statistical analysis initially verified the data distribution of each variable Kolmogorov-Smirnov test and homogeneity of variances Levene test.
Assumptions of normality of distribution in each group and homogeneity of variances among the groups were tested using the Shapiro-Wilk test and Levene's test, respectively.
The Kolmogorov-Smirnov test was applied to the numerical variables to check the normality of numerical data, andthe Levene test to check the homogeneity of variances.