Univariate environments

Univariate Verses Multivariate. The problem of working in univariate or multivariate environment was addressed in only one comment even though a whole book could be written on this topic alone. "Analysts should change their direction, wherever they can, to work in a multivariate area." Dr. Stalling said, "And the thing that impresses me so much about the chemometrics potential, is the capability of using multivariate statistics. How many problems can you define in the real world better in a univariate way Name me one "... 

In addition to univariate statistical analysis, the data were also examined by means of multivariate statistical techniques. In particular, R-mode factor analysis was used, which is a very effective tool to interpret anomalies and to help identify their sources. Factor analysis allows grouping of anomalies by compatible geochemical associations from a geologic-mineralogical point of view, the presence of mineralizing processes, or processes connected to the surface environment. Based on this analysis, six meaningful chemical associations were identified (Fig. 15.8). 

Felhofer et al. (46) reported an application describing the separation of five bisphenols (bisphenol E, bisphenol A, bisphenol AP, tetramethyl bisphenol A, and bisphenol P) by MEKC. It has been well established that bisphenols can reach the environment, and also the human body (47). Bisphenols are widely employed in the manufacture of plastics, especially those used in food and beverage packages, baby bottles, and water supply pipes. In this study, a univariate approach was first developed using a BGE composed of borate, SDS, and acetonitrile. The goal was to achieve the best separation of the... 

Figure 2.3 shows the effect of applying these CNS leadlike filters to an in-house data set of298 compounds. As the aim was to demonstrate how a conventional lead differs from a CNS lead, aH compounds in the data set were compliant with the leadlike filters specified by Oprea et al. [49]. A univariate analysis was performed with all 2D descriptors available in the Molecular Operating Environment (MOE) program, and the most highly correlated individual descriptors (TPSA, vsa pol, vsa acc) were related to surface polarity. 

Raman Spectroscopy Historically, Raman spectroscopy was never considered a sensitive technique because only 1 in 10 photons emitted from a molecule is collected. However, Raman systems have improved tremendously in the last several years. It is no longer deemed an insensitive, irreproducible, fluorescence-dominated technique. Raman is a versatile technique capable of providing information on several parameters simultaneously, such as monomer concentration and particle size. Raman is especially amenable for monomer detection in water-soluble polymers because symmetric vinylic monomer structures are good Raman scatterers and water has a weak signal. To that end, Raman is a complementary technique to FTIR and can be used to monitor monomer concentration and conversion. By employing a near-IR laser (785 nm) which removes most of the fluorescence, along with sharp monomer and polymer peaks that are often separated, monomer concentrations may be determined with univariate calibration. Additionally, since Raman is sensitive to the local molecular environment, it may be used to provide particle size information. 

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