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Based on analysis of variance, significant differences between diploid and tetraploid Triticum species were found.
In multifactorial analyses of variance, significant influences were found for age, gender, education, household net income, residence, and federal states.
Data were analysed using factorial analysis of variance; significant interactions were examined with simple main effects analysis using the non-pooled error term (Howell, 2002, p. 490).
According to initial analyses of variance, significant effects of event (p < 0.0001) and gender (p < 0.05) were present in analyses of all types of examinations, except for hooves, where no significant gender difference was found [ 11].
Between-group comparisons of CHBQ total scores and overall CAM modality use were made by one-way analysis of variance; significant F-tests were followed by pair-wise, independent t-tests.
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Levene's Test for Equality of Variances significant; thus, equal variances not assumed for t-tests.
Besides the small moderation effects on the variances, significant effects of the moderators on the means were observed in this study.
Finally, though between-hospital variance was significant overall, but in most cases pairwise differences between hospitals were not significant.
The analysis of variance demonstrated significant differences between only designs R and C (P=.031).
Repeated measures analysis of variance revealed significant effects of treatment and time on Rs.
Analysis of variance revealed significant gains for both types of relation.
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