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Figure 8 Linear regression plots.
Fig. 3 Linear regression plots between QGS and CMR of LV volumes (a) (blue circles indicate EDV; red indicates ESV) and EF (b) Fig. 4 Linear regression plots between cREPO and CMR of LV volumes (a) and EF (b) Blue and red circles indicate as the same as Fig. 3.
Three low-level standard and blank solutions were prepared and analyzed on three different days to build linear regression plots that were used to estimate both the limit of detection (LOD) and limit of quantification (LOQ) according to mathrm{L}mathrm{O}mathrm{D} = (3.3s kern0.1em /kern0.1em b (1) mathrm{L}mathrm{O}mathrm{ Q = (10s)kern0.1em /kern0.1em b (2).
Linear regression plots (Figure 3) of undifferentiated ES cells demonstrated much higher correlation to the EB stage (r = 0.91) than to the OL sage (r = 0.70).
IC50 was calculated using linear regression plots.
The linear regression plots are shown in Figure 3a and Figure 3b.
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Values of qmax and b (KL/qmax) are determined by the linear regression plot of (Ce/qe) versus Ce.
A standard linear regression plot and equation was extrapolated from the mean fluorescence intensity (MFI) of the control beads.
The best CDM prediction is against the winter historic data, which shows a linear regression plot with slope of 0.99, intercept of 0.0212, and R2 = 0.872.
The relation was represented by linear regression plot of ln (chromite mass) versus Ln (lo) with high correlation coefficient (R 2 = 1) in Fig. 5b.
The injection amperometric investigation confirms the highest selectivity of 284 mA g−1 μM−1 is attained, according to a linear regression plot of current response versus glucose concentration, i.e., 0‒1 mM.
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