Ai Feedback
Exact(4)
Data were initially screened for normality and homogeneity of variance prior to analysis of variance (ANOVA).
Data were screened for normality of distribution and homogeneity of variances using a Shapiro-Wilk normality test and the Barlett's test, respectively.
The data for both groups was screened for normality of distribution using Wilks-Shapiro W statistics.
Further, all outcome data will be screened for normality and, if necessary, logarithmic transformations or non-parametric methods of analysis will be applied.
Similar(56)
Groups were pre-screened for normality and compared with either a Student's t test or Mann-Whitney U test.
Surprisingly and in remarkable contrast to the results observed for Strategy I, samples from the uniform distribution that had passed screening for normality of residuals also led to conditional Type I error rates that were far above 5%.
This evaluation was additionally motivated by the anticipation that, although the observed conditional Type I error rates of both the main parametric test and the nonparametric test were seriously altered by screening for normality, these results will rarely occur in practice because the Shapiro-Wilk test is very powerful in large samples.
Histograms and descriptive statistics for the individual variables were screened for deviations from normality.
Data consistency was checked and data were screened for outliers and normality by using quantile plots.
Before analysis, data were screened for gross deviance from normality.
All items were screened for univariate and bivariate normality, and to detect outliers.
Related(16)
screened for standard
inspected for normality
tested for normality
screened for natural
scrutinised for normality
testing for normality
screened for prostate
screened for risk
screened for intelligence
screened for combat
screened for heart
screened for hemolysis
screened for haemolysis
screened for resettlement
screened for radiation
screened for character
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com