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The study said this was an underestimate because the data did not capture poor households who eschewed charity handouts or used only state-funded welfare services Julia Unwin, chief executive of JRF, said: "It is simply unacceptable to see such levels of severe poverty in our country in the 21st century.
Because the data did not pass the Kolmogorov-Smirnov test (Ds = 1.00, ps < 0.0001), we compared the demographic data of Jalal et al. (2015) and our replication study using the Mann–Whitney U-test.
Regarding the other two item types (i.e., Dis and Non), because the data did not meet the normality assumption, Kruskal Wallis tests were performed, with Mann–Whitney U tests as follow-up procedures whenever applicable (the alpha level was adjusted to.017 with Bonferroni corrections).
Regarding the effects of implicature type on test performance, because the data did not meet the normality assumption, Friedman tests were performed, with Wilcoxon tests as follow-up procedures whenever applicable (the alpha level was adjusted to.017 with Bonferroni corrections).
Non-parametric methods were used because the data did not conform to parametric assumptions.
Because the data did not follow typical Gaussian distribution, a nonparametrical test (two-tailed, 95% confidence, Mann-Whitney test) was used to determine statistical difference between the groups.
Similar(36)
We refrained from performing an ANOVA because most of the data did not show a Gausian distribution.
All statistical tests were applied two-sidely and non-parametrically because analysis of the data did not show a normal distribution.
We summarised the findings narratively because the nature of the data did not allow a meta-analysis to be conducted.
Continuous variables were expressed as the median with interquartile ranges because the majority of the data did not follow a normal distribution.
A power of unity (S+− = 1) is used because the data do not constrain this parameter well.
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