Sentence examples for for normal distributed from inspiring English sources

Results were analysed using the SPSS version 11.5 and were expressed as median (minimum maximum) for non-normally distributed data and as mean ± SD for normal distributed data.

Comparisons were made between treatment arms using Students t tests (for normal distributed continuous data) and Mann Whitney U tests (for non-normally distributed continuous data).

For descriptive purposes, mean values and standard deviations were used for normal distributed data, and range and medians for data with a skewed distribution.

Briefly, after assessing for normal distribution (using the Kolmogorov Smirnov test), comparison between two groups, if not otherwise stated, was performed using a two‐tailed unpaired t‐test for normal distributed data or a Mann–Whitney U‐test for nonparametric data.

Differences between historical and recent data were tested for significance with the paired t-test for normal distributed data and Wilcoxon signed rank test for non-parametric data.

Statistical significance for normal distributed samples was analyzed by unpaired t-test.

Student's t test was used for comparisons of normal distributed continuous data and the Mann–Whitney U test and Kruskal Wallis test were used for comparisons of non parametrically distributed data.

Analysis of variance (ANOVA) was used to show an overall difference between groups, the Student t test for pairwise comparison of normal distributed parameters, and the Mann–Whitney U test for parameters without normal distribution.

In the last two decades several methods for detecting RTM have been developed both for the case of normal distributed data [ 8, 9] as well as for the non-parametric case [ 10, 11].

Data were first analysed for normal distribution; normally distributed data were analysed by one-way ANOVA and then treatment groups were compared using TUKEY post hoc analysis.

Appropriate tests were performed (Kruskal-Wallis ANOVA followed by Dunn's Multiple Comparison Test (figure 1 and 2), Spearman rank test (figure 4, figure S4) for the non-normal distributed data) and t-test for the normal distributed data (figure 3)) depending on properties of respective data.