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In this study we found 9% (n= 13) were good migraine predictors and 27% (n=40) were defined as bad migraine predictors (Table 1), and both groups stood up as different from the rest of the sample with statistical significance (p<0.001).
The size of the STAR*D study provides a clinical sample with statistical power to detect moderately sized genetic influences.
We use a Support Vector Machine [35] approach implemented in the statistical programming language R [36] to classify a given sample with statistical accuracy.
The NearestTemplatePrediction algorithm (NTP) [ 27, 28] was used to predict the class of a given sample with statistical significance (false discovery rate, FDR < 0.2) using a predefined set of markers that are specific to multiple classes (TB interface vs. TA area).
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We determined DPPH scavenging activity and Fe2+ chelating assay by abundant samples with statistical results without the usage of BHT.
The study of multiple samples with statistical methods has led to different ideas about the paper maintenance and identified interesting problems related to the design of experiments, highlighted by the importance of storage conditions.
All comparisons were based on 10 saline-treated and 10 cocaine-treated samples, with statistical significance inferred at p<0.05 or better.
Statistical analysis was performed using non-parametric tests for two independent samples with statistical significance set at p < 0.05.
The results were analyzed using the t-test for two correlated samples, with statistical significance at P ≤ 0.05.
A positive correlation between EMP3 protein expression as detected by either IHC or WB analysis was found on 43 tumor samples, with statistical significance (P = 0.0038).
Among samples taken from cleaned compartments (S1 and S7), the feed line was the only sample, that with statistical significance predicted whether VRE could be detected in any sample from the compartment at that sampling occasion (χ2 test, p = 0.05).
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