The F-statistic of the model is highly significant ( p < 0.000 with 18; 5501 degrees of freedom), meaning there is a significant relationship between expected household consumption and the explanatory variables.
Excerpts
Through a univariate analysis, this issue—“ is there water? how is it available? ” showed a highly significant difference ( p = 0.000) (see Table S1 in the Supplementary Materials ) between markets.
However, when tested by the independent two-sample t -test (2-tailed), the difference in CO 2 concentrations before and after the ventilation improvement is statistically extremely significant at the 100% confidence interval ( p = 0.000 in Classroom 1, 387 and 740 measurement points; p = 0.008 in Classroom 2, 387 and 718 measurement points).
The relationship between the two dependent variables was also analysed, and a highly significant correlation was found between BMI z-score and body fat percentage (r = 0.539, p = 0.000). 3.3.
In all four research areas, only the dependencies on the variables of the age of the respondents and their length of service turned out to be statistically highly significant ( p ≤ 0.000).
The entire table also indicates a highly significant and positive ( p = 0.000, T b = 0.458) association between social inclusion and participation in decision making for both genders.
The correlation coefficients for these corrected worry-annoyance relations, based on individual scores, are all three highly significant ( p = 0.000). 3.3.
When comparing the scores, highly significant differences in the affective evaluations were reported for the motivational quote/comic comparison (T = 7.392, p = 0.000) and the influencer/comic comparison (T = 4.950, p = 0.000).
Regarding nurses’ knowledge, the current study showed that there were highly significant differences in knowledge mean scores between pre- and post-implementation of a standardized protocol for oxygen therapy ( p = 0.000).
They demonstrated highly significant differences in the standard scores of the three groups on the neuroticism dimension, F(2, 87) = 281.104, p = 0.000.
The proportion of children affected by moderate or severe stunting showed an increase with age, this increase was shown to be highly significant ( p = 0.000), between the youngest age group versus the older age groups, respectively.
However, tested by the independent two-sample t -test ( Table 6 ), the difference in medians was statistically extremely significant at the 100% confidence interval ( p = 0.000, 2-tailed).
Board-moisture content had a highly significant effect ( p = 0.000), while the effect of particle fraction on formaldehyde content ( p = 0.806) had no statistical impact.
The analyses performed using the Mann–Kendall test for the proportion of TB/HIV coinfection among men ( Figure 13 a,b) revealed a highly significant upward trend ( p < 0.000).
The coefficient of the spatial auto-correlation was 0.55, which is highly significant in the models with p = 0, indicating the apparent neighborhood effects.
First, a modified t-test reduced the effective sample size to 11,010.13 (df = 11,008.13), yet the corrected test statistic remained highly significant (t = 36.84, p = 3.06 × 10 −280 ).
Similarly, the prevalence of typhoid was notably elevated in Bumbu (91.3%) compared to Bandal (77.4%), with a highly significant X 2 result ( p < 2.2 × 10 −16 ).
One notes highly significant terms for time (β-est. = 0.21, (95%C.I. 0.17, 0.25), p < 2.2 × 10 −16 ), monthly cannabis use (β-est. = 2.97, (1.91, 4.03), p = 8.2 × 10 −8 ), cannabis use quintiles (β-est. = 3.86, (2.45, 5.27), p = 1.2 × 10 −7 ), dichotomized cannabis use quintiles (β-est. = 3.54, (2.19, 4.89), p = 4.4 × 10 −7 ) and time: quintile interactions. 3.4.
Importantly in an additive model with the other four drugs cannabis use is highly significant (β-estimate = 0.45 (0.32, 0.57), p = 7.24 × 10 −12 ).
A significant trend was found (Chi Squ. = 312.2, df = 164, p = 2.63 × 10 −11 ). 3.8.2.
II difference was highly significant ( p = 6 × 10 −11 ).
We find a highly significant improvement in model performance (R 2 of 0.035 vs. 0.14, p < 10 −10 ). 3.2.
All results were highly significant with p < 0.000001.
This difference was highly significant ( p < 0.00001, Chi-square test).
The overall pooled effect size of acculturative stress in the intervention group was not significantly reduced versus control [mean difference: −0.36 (95% CI: −0.72, 0.00) at p = 0.05] with a highly significant difference in the heterogeneity (I 2 = 81% at p < 0.00001) ( Figure 4 a).