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If data met assumptions for normality, tested with the Shapiro Wilk test, t-tests were run with or without Welch's correction depending on the homogeneity of variance (tested with Levene's test).
The primary dependent variables met assumptions for analysis of variance (ANOVA), and were approximately normally distributed (|skewness| <2.0, |kurtosis| <2.0).
The primary dependent variables met assumptions for ANOVA, and were approximately normally distributed (|skewness| < 2.0, |kurtosis| < 2.0).
All other data met assumptions of parametric statistics.
I tested data for normality (Shapiro-Wilk test) and equal variance and used parametric tests for data that met assumptions; otherwise I used non-parametric statistics [36].
Quantitative variables were compared between groups with and without virologic rebound by exact Wilcoxon two-sample non-parametric tests because of the uncertainty of whether the small sample met assumptions of a normal distribution.
Similar(41)
Euclidean distance values were square-root transformed to meet assumptions of normality and homoscedasticity of ANOVA.
Prior to analysis, the mean ages of fine roots determined by counting the number of annual growth rings were log10 transformed to meet assumptions of normality.
It turned out that the distance between the points was not meeting assumptions of the method.
For ANOVA on the time to second-degree burn the data was log10 transformed to meet assumptions of normality.
Data were arcsine-transformed to meet assumptions where necessary.
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CEO of Professional Science Editing for Scientists @ prosciediting.com