Correlation coefficient composition determined

The results observed with a representative set of test-liquids are recorded in Fig. 11. The square of the correlation coefficient (r2), determined by linear regression analysis, was in every case >0.99 when the slope was >1, but r2 for those with slopes less than 1 were sometimes less than 0.98, owing to decrease in accuracy as a result of decrease in the difference (S — v) where v is the porosity characteristic of the respective composite film samples. In such cases the determination was repeated to obtain sets of averaged values, which typically exhibited r2 > 0.99. 

The RGB composite of the coefficients of determination of the individual linear correlation coefficients (Figure 2.26) shows that for the northern hemisphere high correlations of volatilisation rate and wind speed in the Atlantic Ocean can be found in the Gulf Stream and low values in the Labrador Sea and the adjacent Davis Strait. High correlations with the sea surface temperature are located near 45 °N close to the eastern coast of the American continent, in the Baltic Sea, North Sea and in... 

Structural Effects and Solvent. The effect of solvent on the equilibrium of Reaction 4 can be first discussed in terms of effects on the susceptibility to substituent effects. The values of pK2, characterizing this equilibrium, are a satisfactorily linear function of the Hammett constants correlation coefficient r (Table VI). The values of reaction constant p are practically independent of the ethanol concentration (Table VI), as was already indicated by the almost constant value of the difference (A) between pK2(H20) and p 2 (mixed solvent) for a given composition of the mixed solvent (Table I). The same situation is indicated for DMSO mixtures (Table II) by the small variations in A for any given solvent composition. In this case, the number of accessible p 2 values was too small to allow a meaningful determination of reaction constants p. The structural dependence for various water-ethanol mixtures is thus represented by a set of parallel lines. The shifts between these lines are given by the differences between the pK2H values (p 2 of Reaction 4 for the unsubstituted benzaldehyde) in the different solvent mixtures. 

This method can be extended to fairly complex peak clusters, as presented in Figure 6.26 for die data in Table 6.2. Ignoring die noise at die beginning, it is fairly clear diat there are three components in die data. Note diat die central component eluting approximately between times 10 and 15 does not have a true composition 1 region because die correlation coefficient only reaches approximately 0.9, whereas the odier two compounds have well established selective areas. It is possible to determine the purest point for each component in die mixture successively by extending the approach illustrated above. 

Ogawa established that the compositional distribution, the correlation coefficient and the molecular mass distribution were important in determining the variation in composition observed across the chromatogram (using a dual detector system). Molecular mass distribution affects the compositional variation, as does the correlation coefficient. The broader the molecular mass distribution, the less is the compositional variation. The greater the compositional distribution, the more compositional variation is observed in the SEC... 

Thermal conductivity derived in Eq. 6.14 is plotted and compared with the experimental data of GSA-SDS/FMWNT composites as in Fig. 6.12. The predicted values of the composites differ by 0.003 0.002 W/m-K which is marginally small for a temperature profile from 290 to 370 K. Correlation coefficient is a numerical measure of the strength of the relationship between two random variables. The value of correlation coefficient varies from -1 to 1. A value close to +1 or -1 reveals the two variables are highly related. Pearson s product moment correlation coefficient measures the linear relations between two data sets and was determined to be 0.935 between the predicted model (Eq. 6.14) and the experimental data. 

PVAc has been determined according to equation Tg = 18.4 - 6.77C + 0.2197C (plasticiser content C in % validity range 0-12.5% correlation coefficient 0.9986) [85]. Whereas further chlorinating (PVCC) increases Tg from approximately 86°C towards 100°C, it can be lowered to almost any value by addition of plasticisers (-40° to +90°C), as indeed is true also for PVAc. When the additive concentration in a resin exceeds a few weight percent, it is often possible to assay the additive calorimetri-cally without extracting it. If the additive is incompatible with the resin, it can be detected in a separate crystalline or glassy phase by either its Tm or Tg and measured quantitatively from A7/f determinations at Tin or Acp measurements at Tg. When an additive is soluble in a polymer, its concentration can be estimated from shifts in Tm or Tg of the resin. Once a master curve of Tg V5. plasticiser concentration has been prepared for a particular PVC composition, it can be used to determine the amount of plasticiser in an unknown formulation of the particular plasticiser, e.g. PVC/DIDP (cfr. Fig. 2.1) [27]. For PVC/DOP a linear relationship from zero to 45 wt.% plasticiser has been reported [86]. DSC was also used in miscibility studies of erucamide and PA 12 [87]. 

Correlation coefficients calculated in a similar manner for multiple pairings of radioelements can be included as input into the PA sampling routine, allowing the value selected for one radioelement sorption parameter to be conditioned by its geochemical relationship to the other radioelements. Theoretically, for a given water composition, sorption coefficients of two or more radioelements should be determinate based on the geochemical controls on their. sorption behavior. In this sense, the soiplion c )ellicienls are deterministically correlated, rhe.se ty XJs of cor-... 

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