The multiplier generally decreases with increasing sample size; however, we observe that a nonlinear relationship between sample size and betweenness produces a bump in the three curves involving betweenness.
This inverse relationship between sample size and magnitude of sampling errors can be illustrated by referring again to tossing a coin.
Finding a compromise between sample size and accuracy of sample estimators is therefore of crucial importance.
Tests for correlations between sample size and taxonomic relative abundance are commonly used in zooarchaeological analyses to determine whether observed trends in relative abundance might simply be the result of sampling error.
For eQTLs, we observed a strong correlation between sample size and the proportion of loci with AH (R2 = 0.85, p = 2.2 × 10−16), indicating that statistical power prevents identification of AH in other loci.
This is because the conditions that are most conducive to correlations between sample size and relative abundance are quite different from the conditions that will lead to erroneous conclusions about the presence or absence of a trend in relative abundance.
Among simulated sets of sample assemblages, significant correlatoins between sample size and relative abundance are distributed randomly with respect to whether or not Type II errors concerning trends in relative abundance are present, and are underrepresented in cases in which Type I errors are present.
We also considered the relationship between sample size and number of items, since this is considered an important methodological aspect to be evaluated during the scale development process.
The balance between sample size and number of variables is causing the minimax estimation to converge at a minimum that allows a fairly high Pfa while maintaining an effective characterization of the background spectra.
Thus, we essentially perform statistical sampling which is a common technique for example in opinion surveys and for which the relationship between sample size and the accuracy of the estimate is well understood.
Naro-Maciel et al. (2011) analyzed divergent lineages observed within Caribbean spiny lobsters to investigate population differentiation, and found that although intraspecific divergence may have been underestimated in some cases due to smaller sample sizes, there was no significant correlation between sample size and mean intraspecific divergence.
