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Correlation coefficients assess the association between two continuous distributions.
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A Pearson correlation coefficient was calculated to compare linear relationships between two continuous variables with Gaussian distributions; a Spearman coefficient was calculated when non-Gaussian distributions were noted.
Comparison between two continuous variables of normal distribution was carried out using the t-test.
Comparison between two continuous variables, which had a non-Gaussian distribution, was performed by applying the Mann–Whitney non-parametric test.
We tested normal distribution by the Kolmogorov-Smirnov-Test. Wilcoxon-matched-pairtest and Mann-Whitney-U-test were applied to analyse differences between two continuous variables.
Pearson's r measures the association between two continuous variables.
Using a consistent cut-off in both studies also increased comparability between them as continuous distributions were likely to differ between the two cohorts.
The Poisson distribution is very important in understanding biological processes and provides a link between discrete and continuous distributions.
The non-parametric Kruskal Wallis test was used to compare continuous distributions between two groups.
randomly distributed data) we expect γi to follow a Gaussian distribution with mean μ and standard deviation σ, given by: These expressions follow from the mean and standard deviation of the difference between two uniformly distributed continuous random variables.
We derive general mathematical properties of a new continuous distributions with three extra shape parameters.
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