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The Mann-Whitney U test was used to compare differences between non-normally distributed variables.
Differences between normally distributed continuous variables were assessed using Welch's t test, and between non-normally distributed continuous variables using Wilcoxon rank-sum test.
Spearman's correlations were calculated to explore relationships between non-normally distributed continuous variables.
Spearman correlations were used for evaluation of the association between non-normally distributed data.
The Spearman correlation was used to assess correlations between non-normally distributed continuous variables.
Differences between non-normally distributed variables were tested using the non-parametric Mann–Whitney test.
Differences between normally distributed variables were assessed using Welch's t-test; differences between non-normally distributed continuous variables were assessed using the Wilcoxon rank-sum test.
Comparisons between non-normally distributed continuous variables were performed by either the Kruskal-Wallis test or the Mann–Whitney U test, depending on the number of comparison groups.
Differences between normally distributed variables were assessed using Welch's t-test; differences between non-normally distributed continuous variables were assessed using Wilcoxon rank-sum test.
Differences between non-normally distributed groups (or groups that failed the test of equal variance) were evaluated using the Mann–Whitney Ranked Sum Test, and two way repeated measures ANOVA (Temperature experiments).
Student's t test was used to compare normally distributed cytokine concentrations between the patients and controls, while the Mann Whitney Wilcoxon test was used for non normally distributed data.
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