Sentence examples for data is explored with from inspiring English sources

The influence of additive Gaussian noise on the response data is explored with respect to the quality of the resulting parameter estimates.

Aside from the analyses reported, several possible structures in the data were explored with principal component analyses (PCA).

Comparisons between the genetic groups for the continuous descriptive data were explored with analyses of variance (one-way ANOVA).

Final harvest data were explored with linear and non-linear regression including logistic sigmoid and logistic with hormesis approaches (Stephenson et al. 2000), with the models selected being those with lowest variance of residuals.

Quantitative data was explored primarily with descriptive statistics.

The data were explored for fit with the assumptions required for a multivariate analysis.

The elimination rate constant was estimated using the plasma concentrations at the end of and after open-label study drug administration, and the data were explored for a trend with age, using linear regression analysis and tests for trend.

Themes emerging from these data were explored by in-depth interviews with a sample of 18 childcare providers and 7 Local Authority Early Years Service staff.

Sensitivity of the results to imputation of missing data was explored by running the models with and without imputation.

The bias in the approximated variances is explored with MODIS-NDVI data.

However, the impact of missing data was explored for the four families (2.6 %) with partial data (7-month data available but not 13-month), using the last value carried forward.