Sentence examples for variable data analysis from inspiring English sources

It is worth noting that combined use of multivariate data (i.e., seismic, geodetic, tsunami, and so on) possibly compensates for the weakness of single variable data analysis during great events with complex disasters.

In this paper, we propose a multi-variable data analysis algorithm based on the Radial Basis Function (RBF) neural network methods to estimate coal quality parameters from routinely-acquired, multiple geophysical logs, such as density, gamma ray and sonic.

Considering the potential influence of individual body mass differences on dietary intake variables, data analysis was performed on total values and adjusted for body mass [5, 6, 41].

These findings proved that the proposed method was appropriate for variable streaming data analysis, thereby demonstrating the effectiveness of the proposed method.

The Kaplan-Meier method was used for single variable survival data analysis.

Because, as shown in Figure 1, the mean miR-146a expression in the baseline and postexposure blood samples did not show significant differences, we also evaluated the associations with lead and cadmium exposures in mixed regression models that included both sets of miR-146a expression measurements as the dependent variable (pooled data analysis of baseline and postexposure miR-146a expression).

Given that there is no 'one size fits all' CE model, health interventionists using CE models should include measurements of CE in addition to other variables in data analysis to demonstrate its relationship to the outcome variables.

The occurrence of bacterial isolates from the ophthalmic samples and their antimicrobial susceptibility pattern were used as dependant variables where as age, sex, occupation, educational status, and residence were used as independent variables during data analysis.

Simultaneous analysis of all observed variables: multivariate data analysis, principal component analysis, correlations analysis, factorial analysis and clustering Multivariate comparisons of the different variables: hypothesis testing, multiple ways ANOVA, MANOVA, and others to determinate if the groups differ relative to the different questions: specific GMO effect or diet effect per se.

Simultaneous analysis of all observed variables: multivariate data analysis, principal component analysis, correlations analysis, factorial analysis and clustering.

Measures of visual search behavior (search rate and fixation location; see the "Dependent variables and data analysis" section below) were calculated using the Tobii Studio version 3.2.1 software.