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This pattern is clearly compatible with the adoption of different strategies in relation with gender determining significant differences in performance.
We repeated this analysis with different cut-off p-values (for determining significant differences in gene expression) and found that this pattern remains significant down to a p-value of 0.001 (below which there are insufficient data for meaningful comparisons).
This is a nonparametric test useful in determining significant differences for more than two independent groups for ordinal dependent variable (Pallant 2007).
The thresholds for determining significant differences in gene expression were a FDR (false discovery rate) ≤ 0.001 and an absolute value of log2 Ratio ≥1.
After determining significant differences and the false discovery rate (FDR) in the analysis, the differentially expressed genes were selected according to the P value threshold.
All data are presented as the means ± SD, followed by determining significant differences using the two-tailed t test or ANOVA test.
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One-way analysis of variance (F-test with p < 0.05) is performed to determine significant differences between different treatments.
A χ test of significance was used to determine significant differences between cross-tabulated proportions.
The chi-square test was used to determine significant differences in the ARI scores among the different groups.
The chi-square test was used to determine significant differences in the adhesive remnant index scores among different groups.
Chi-square analysis was performed to determine significant differences in NaCl-promoted bioformationation between MRSA and MSSA strains using Microsoft Excel.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com