Sentence examples for power of variance from inspiring English sources

The improvement from these works can be divided mostly into three categories as follows: (i) adjust fixed block effects and degrees of freedom in F test, (ii) improve the power of variance homogeneity tests, and (iii) develop a robust test that can be applied to non-normal distributions.

Decreasing residuals with increasing initial length was modelled by including a power of variance function with initial length as covariate.

The performance of the combined test largely depends on the power of the variance test: it outperforms the standard test when the variance test has any power and thereby contributes to the combined test statistic.

The consequences of such variability in growth on experimental designs and power of analysis-of-variance models are discussed.

The final model has the strongest explanatory power, explaining 15.1% of variance (measured using Nagelkerke's R).

A power analysis (analysis of variance [ANOVA]) indicated that six animals in each group would be enough to detect a pH difference of 0.1 with a standard deviation of 0.05 with a p <0.05 and a power of 0.8, assuming a normal distribution.

DPPH: 1,1-diphenyl-2-picrylhydrazyl; TPTZ: 2,4,6-tris 1-pyridyl -1,3,5-triazine; EC: Electrical Conductivity; TDS: Total Dissolved Solids; HMF: 5-hydroxymethylfurfural; HPLC: High Performance Liquid Chromatography; CEQ: Catechin Equivalents; DCPIP: 2,4,6-tris 1-pyridyl -1,3,5-triazineutylated Hydroxy Toluene; FRAP: Ferric reducing/antioxidant power; ANOVA: Analysis of Variance.

Corrections to the discrete case in terms of powers of the variance can often be obtained.

The power spectra of the resulting trend and IMFs were estimated via the construction of a periodogram, which is a graphical representation of the distribution of power (or variance) among different frequencies, the inverse of the period of cycles per year.

In order to calculate the required information size and the cumulative Z-curve's eventual breach of relevant trial sequential monitoring boundaries [17], [18], the trial sequential analysis was based on a type I error of 5%, a beta of 10% (power of 90%), the variance of all the trials (as no trial had low risk of bias), and a minimal relevant difference of 2 points on the HDRS.

Sample size was calculated for the Pediatric Evaluation of Disability Inventory (PEDI) (based on data from an earlier study [ 31]; with a subgroup analysis of children of 2-3 years) using the following assumptions in a one-way analysis of variance power analysis (based on a power of 80% and a two-sided α-value of 0.05).