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All pairwise contrasts between populations were significant (P < 0.05).
Overall, 27 out of 105 pairwise ΦST comparisons between populations were significant.
All pairwise comparisons of genetic differentiation between populations were significant (P < 0.05) (Tables 3 and 4).
To assess whether differences between populations were significant, we used the Welch t-test [ 3], which tests the null hypothesis that two populations have the same mean value, without assuming equal variances.
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In general, genetic variation between populations is significant, even among nearby populations.
The genetic differentiation between populations was significant in four of the ten pairwise FST values (Table 4).
However, when the heterogeneity of MSRs between populations was significant, no MSR showed consistent behavior, where e.g. lengths were always shorter in a certain population compared to another population.
Combined models using pooled data from both cities with an interaction term indicated that the differences between the two populations were significant for the reduction in annual cardiovascular mortality (males and females combined) and for annual all cause mortality in men (see appendix 2).
All the differences between insured and uninsured populations were significant in both surveys.
*All of the differences comparing prevalence of comorbid conditions between commercial and Medicare populations were significant (p < 0.01), using two-tailed, chi-squared analysis, except for those indicated by italic text.
All comparisons between East and West/Central Atlantic populations were significant (ΦST = 0.621 – 0.740), reflecting an evolutionary genetic partition (sequence divergence d = 0.88% – 0.98%).
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