Sentence examples for analysis for explaining from inspiring English sources

This message was sorted under casualties as "basic data" for identifying how many casualties and "analysis" for explaining how the casualties occurred.

As in [ 24], these studies also include considerations of deterministic representations of flux analysis for explaining the behavior of stochastic systems.

Furthermore, we came up with a version that demonstrated authentic biological value: the implications of the scaling analysis for explaining the value of certain variations and the implications for a deeper understanding of phylogenetic development (of gills and lungs).

The model of multiple linear regression used to identify factors associated with ΔZ-scorew at 36 weeks PCA/DC has a quite poor general coefficient, suggesting that other variables not considered in the analysis may account for explaining the growth outcome in the studied population.

It's based on the belief that the tools of economic analysis are really useful for explaining things in the real world.

Therefore, a parametric push-out analysis was carried out for explaining the fatigue behavior of group studs, particularly the low cycle fatigue aspect with the fatigue life lower than 2 million cycles.

This initial description and analysis may be important for explaining different responses to treatments at different farms.

Analytic memos were written throughout, providing both a record of the data analysis process and a framework for explaining the results of the analysis.

Overall, the global sensitivity analysis proved a powerful tool for explaining and quantifying uncertainties as well as providing insight into devising useful ways for reducing uncertainties in the plant performance.

Hence, this analysis provides a rational basis for explaining the higher Ki compared of this PLM versus those of JTH-NB72-35 JTH-NB72-35 JTH-NB72-35

The new method for defining the linear granulometric function proposed in this study is based on principal component analysis (PCA), which is a technique for explaining the correlation between multiple variables and accounting for a large variance using only a few synthetic variables (principal components) (Davis 1986; Middleton 2000).