Accordingly, an attempt was made to find the theoretical distribution models which fit well to headway data: log-logistic, lognormal, Pearson 5 and Pearson 6 distributions were considered in the present study.
Normality was checked for all variables under study using D'Agostino-Pearson testing, and paired two-tailed t tests were used to compare group means with p < 0.05 defined as significant.
In the relationship between work stressors and work adjustment, this study used a bivariate Pearson-product moment correlation analysis to test the association between constructs.
test with Yates' correction; + Exact (Clopper-Pearson) 95% confidence interval a includes study that only reported either sensitivity or specificity; b,c.
Thus, the present study considers four distributions namely, log-logistic, lognormal, Pearson 5 and Pearson 6 for headway modelling at moderate and heavy flow of traffic.
Table 1 Demographic variables and pearson-product moment correlation matrix for each study variable Mean 95% CI 1 2 3 4 5 6 7 8 1. Headache frequency (days/month) 18.1 18.1–18.1 2.
In conclusion, the study shows that the RMA-Pearson method has better coverage of the coexpression landscape and the MAS5-Spearman is more accurate to find coexpression pairs.
D'Agostino-Pearson testing demonstrated normality for all variables under study (p > 0.1).
Further, the Pearsons correlation coefficients for physico-chemical parameters of water in the study area are presented in Table 2.
