Sentence examples for using multivariate statistical approaches from inspiring English sources
This study represents the first attempt to identify relationships between the availability of Cu, Zn and Cd assessed using DGT technique and several representative extractions procedures (aqua regia, diluted strong acid, neutral salt solution, soil solution) and theirs bioaccumulation in food vegetables using multivariate statistical approaches.
The present study was carried out during dry and wet seasons from close by hand-dug wells neighboring Ajakanga solid waste disposal site for better understanding of spatial and seasonal variability of physicochemical parameters, hydro-geochemical facies of groundwater and identification of contamination sources that may affect the groundwater samples using multivariate statistical approach.
Correspondence analysis, a commonly used multivariate statistical approach, was carried out to analyze synonymous codon usage bias.
Mass spectrometry based metabolomics approach can provide significant information about the discrimination between the species using multivariate statistical analysis, classifying chemical groups, discriminate the metabolites with unknown biological potencies [338].
Using multivariate statistical methods, four types were identified.
The method was developed and evaluated through orthogonal experimental design using multivariate statistical analysis.
The pollution sources in the soil were examined using multivariate statistical analysis and Pb-Sr isotope tracing technology.
In this study, we used several multivariate statistical approaches to analyze the metabolites present in the liquid phase (fecal water) of the same fecal samples examined earlier [17].
The experimental procedure was optimized using a multivariate statistical approach and the final analyses were carried out by GC μECD.
We conclude that seascapes, derived using a multivariate statistical approach, are biophysically meaningful subdivisions of the ocean floor and can be expected to contain different biological associations, in as much as different geomorphological units do the same.
Our results suggest that integrating environmental units using a multivariate statistical approach not only produces results in agreement with what we observe empirically, but it also allows us to identify those factors which control the grouping of environmental attributes.
