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This blend of categorical and quantitative modeling permits explanation of differences in variance for different population groups.
We tested for differences in variance between groups with different sex-bias using F-tests.
Like a MANOVA, a permanova is sensitive to differences in variance among groups, particularly when sample sizes differ substantially.
We note that we observe differences in variance among our biological replicates from the different time points.
Differences in variance between males and females were not significantly different from zero (Zsex = −0.03— p = 0.976; n = 96).
Differences in variance due to sex and sociality were not significantly different from zero (Zsex = 1.39— p = 0.17; n = 96; Zsoc = 0.22— p = 0.83; n = 96).
However, when we estimated the differences in variance between 10 RCF litters (estimated across 7 days and 4 different dams/litter) for the amount of received care (factor: litter) by Levene test, we found significant differences neither for NURSING (Levene's 9,60 = 1.14, p = NS) nor for GP/L (Levene's 9,60 = 1.46, p = NS).
The F-test in Past3 [ 49] was used for testing differences in variance detected by analyzing the molecular variance of markers located in different genomic regions (i.e. OUT, UP, IN and DOWN).
Table 2 Gender differences in variance ratios in reading, mathematics, and science Content Level Orga.
There were only marginal sex differences in mean levels of subjective well-being, and no differences in variance.
The F-test was used to determine differences in variance, the T-test to determine levels of significance using Excel.
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