Sentence examples for the parametric tests that from inspiring English sources

These tests are less powerful than the parametric tests that assume data Gaussian distributions.

In contrast to the two parametric tests that assume a specific parametric signal distribution (Gaussian distribution) for the underlying signal series, the Wilcoxon test is non-parametric.

Here we present novel statistics and parametric tests that lead us to reject the models of random rearrangement in favor of directional selection for clustering of functionally related genes in C. reinhardtii.

One general disadvantage of Bonferroni-based approaches is a perceived power loss, motivating the use of weighted parametric tests that account for the correlation between the test statistics or the use of weighted Simes tests.

The random set method introduced in [ 73] is a parametric test that is a generalization of Fisher's exact test in the sense that enrichment scores of gene sets are compared with randomly formed sets.

Similarly, non-parametric tests that directly rely on the shape of the distance distribution functions (e.g. Kolmogorov Smirnov test) will concentrate on the difference in the skewness of the distance distribution functions.

Although previous work found a larger number of protein categories to have elevated FDRs (Huang et al., 2007, p. 497), the current work is based on non-parametric tests that are likely to be more robust.

Wilcoxon rank-sum and Kolmogorov-Smirnov tests are non-parametric tests that evaluate whether two samples of observations come from the same distribution or not.

To meet the assumptions of the parametric tests used (that the residual scores are normally distributed), we squared the test scores and used transformed variables in all analyses.

The Student's t test is a parametric test that calculates a t value that is compared with a critical value to determine whether the difference between the two samples is significant.

GAGE [ 71] (generally applicable gene set enrichment) is also a parametric test that, similarly to GSEA, compares the expression in a target gene set with that of the background.