Sentence examples for testing for uniform from inspiring English sources

Statistical testing for the phase distribution of OFF periods was computed by splitting the data into 10 phase bins and testing for uniform distribution of OFF periods using Pearson's chi-square test – a significant result indicated that OFF periods were not uniformly distributed across the LFP slow wave phases, but rather appeared predominantly at specific phases.

Yarns are tested for uniform thickness and other characteristics; fabric pieces are checked for defects; and the fastness of finishes and colours to various conditions is determined.

Furthermore, three different kinds of representative hydrophilic samples (polystyrene nano-particle aqueous solution, Salmonella bacteria medium, and poly 3,4-ethylenediocythiophene) ink) were tested for uniform depoly 3,4-ethylenediocythiophenephinkc regions.

And more so, it is an improvement over other generalized methods, such as the generalized Mantel-Haenszel method, which only tests for uniform DIF.

The generated random sequences for r 1 and r 2 are tested for uniform random distribution using chi square test to ensure the validity of the simulation using Monte Carlo method.

Data were tested for uniform distribution using three different normality tests (Kolmogorov Smirnov test, D'Agostino and Pearson omnibus normality test and Shapiro Wilk normality test).

IRTLRDIF is based on a hierarchical structure, which means that β ij is tested for uniform DIF, only if the test for α i is not significant.

Polymorphic SNPs were also tested for uniform distribution within single chromosomes after assigning them to 10 Mbp bins according to their chromosome position.

All mapped, good-quality, monomorphic and polymorphic classes of SNPs were individually tested for uniform distribution among chromosomes (with respect to chromosome length in bp) by goodness-of-fit chi-square tests with the appropriate degrees of freedom (df).

The analysis should be done both before and after experimental data collection, first to test for uniform sensitivity on synthetic data constructed with mean values; then a second time, to provide a level of confidence in extracted parameter values and their biological implications.

Crane has suggested testing for non-uniform DIF using a Bonferroni-corrected likelihood ratio chi-squared test with 1 df.