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As only one test statistic (cluster sum of t-values) is tested, the problem of multiple comparisons is effectively taken care of by this method.
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The method is tested on the problem of Kinetic Alfvén wave mediated magnetic reconnection.
The approach was also tested on the problem of scattering from a rigid prolate spheroid.
The resulting scheme is tested in the problem of normal shock wave and that of force-driven Poiseuille flow.
In this case the proposed method is tested with the problem of human recognition based on the face information.
It is well known that there exists an analysis of variance (ANOVA) F-test for the problem of testing the equality of means from several independent samples under the assumptions of normality.
Moreover, regulatory toxicity testing faces the problem of possible false-negative testing.
In contrast, the single-SNP association tests involve the problem of selecting a P-value cutoff after computing P-values to determine significant associations.
In non-targeted forms of testing, the problems of complex information are exacerbated by the enormous quantity of information.
This paper provides an alternative test procedure for the problem of testing normal mean against two-sided alternative with known variance for costly trials.
In order to verify the existence of differences between the average responses of the treatments, when having more than two groups, it is inappropriate to simply compare each pair using a t test because of the problem of multiple testing.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com