Sentence examples for testing for equal means from inspiring English sources

IUTA is the first method to formulate the testing problem as testing for equal means of two probability distributions under the Aitchison geometry, which is widely recognized as the most appropriate geometry for compositional data (vectors that contain the relative amount of each component comprising the whole).

In order to quantitatively investigate whether there is a systematic effect of D s on we apply an one-factor ANOVA test to test for equal means of the for each network type.

For comparison, for each of the 16 axes analyzed using ordered-axis plots we present the results of pairwise parametric tests for equal means (t-tests) and variances (F ratios) based on a table wide α = 0.003 = 0.05/16.

The Wilcoxon rank-sum non-parametric test for equal means between normal and deficient diet groups [ 13] was performed.

For each of the 32 predictions, we perform a one-tailed two-sample t-test for equal means against the DME controls.

For each of the subregions within the PPC (IPS1 IPS7), a circular statistical comparison between the mean phases for the 2 shifted gaze conditions was made using the Watson-Williams test for equal means (Berens 2009).

Statistical comparisons were made with Student's t-test for equal means, if data was normally distributed as assessed using Kolmogorov Smirnov test, Mann–Whitney U non-parametric test was used otherwise.

Baseline characteristics between the low and the high level group of psychotic-like symptoms were compared using a two-sided t-test for equal means for continuous, normally distributed variables and and χ-test for categorical variables.

4. Student's t-test for equal means with the assumption of unequal variance [ 12] was calculated to test for significant differences in signal (expression level) between the normal and vitamin deficient groups.

Finally, Table 2 gives for all false alarm rates between 1 per year and 12 per year the p-values of the test for equal means of BARD's timeliness, x error, y error, and h error over the two simulation groups.

after testing for equal variances and then group mean differences were tested, with P < 0·05 considered significant.