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By help of transgenerational phenotypic data, concrete hypotheses about the extent of epigenomic resetting can be tested on statistical grounds using the experimental framework outlined in this article.
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The quantitative data were analyzed by descriptive statistics (frequencies and percentages) and differences between GPs and nurses were tested on statistical significance (using Chi-squares).
Statistical features are tested on simulated vibration signals.
Five statistical models were tested on data consisting of 10 972 fish that died and 3959 survivors with recorded growth data.
Trends in the proportion of children vaccinated on time were tested for statistical significance using the Cochran-Armitage trend test [ 25].
Differences between the areas under the curves were tested for statistical significance based on the estimated areas and their standard errors.
Tree topology was tested based on statistical methods implemented in CONSEL, and tree distance was quantified using Robinson Foulds metric [ 41] implemented in treedist in the PHYLIP package.
The sample's reproducibility was tested applying a statistical analysis based on a one-way analysis of variance (ANOVA) technique.
Fifty-three concrete mixtures were tested based on a refined statistical analysis.
All data were tested for equality of variances and normality of errors, and statistical tests were performed on untransformed data if these assumptions were met.
All 6 global tests are based on statistical inference instead of permutation.
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