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With nonparametric statistics, data are ranked and the statistical tests compare correlations or differences in mean ranks between groups rather than differences in concentrations.
Analysis was conducted with nonparametric statistics.
Correlations between cystatin C concentration and activity were assessed with nonparametric statistics.
Variables that did not meet the assumption of normality were analyzed with nonparametric statistics.
Variables that followed a normal distribution were analyzed with parametric statistics, and significantly skewed variables, with nonparametric statistics.
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To enable comparison of traditional parametric and nonparametric statistical approaches with nonparametric bootstrap statistics, we report the results of all tests in Tables S1, S2, S3.
In analyses of variables with nonnormal data distributions nonparametric statistics were used.
Results were analyzed using nonparametric statistics with the Mann–Whitney U test.
Nonparametric statistics deals with random observations whose probability distribution is either not known, or unavailable.
The results were analysed using parametric and nonparametric statistics tests, with the SPSS program.
Nonparametric statistics were used with both behavioral and electrophysiological data, because these data were not normally distributed.
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