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The Mann-Whitney U test avoids making distributional assumptions other than requiring group distributions of identical shape.
The distributions of outcome variables will be assessed to determine if distributional assumptions are valid.
Some classifiers make particular distributional assumptions.
Both correct and false distributional assumptions are considered.
Specifically, we checked distributional assumptions and for signs of heteroscedasticity.
This illustrates the goodness of the composite error's distributional assumptions.
None of the tests considered requires structural within-cluster correlation or distributional assumptions.
All scales met the distributional assumptions with skewness and kurtosis values lower than ± 1.
It will differ from classical mechanism design by adopting distributional assumptions about the agents.
Therefore, bootstrapping far outperforms the parametric methods when distributional assumptions are not met.
Bootstrapping is a general procedure for computing CIs without making distributional assumptions [62].
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