Standardization versus single-point

B.2 Single-Point versus Multiple-Point Standardizations ... 

A single-point internal standardization has the same limitations as a singlepoint normal calibration. To construct an internal standard calibration curve, it is necessary to prepare several standards containing different concentrations of analyte. These standards are usually prepared such that the internal standard s concentration is constant. Under these conditions a calibration curve of (SA/Sis)stand versus Ca is linear with a slope of K/Cis-... 

FIGURE 7.17 Dispersion number versus geometric standard deviation A, single point nudeation model B, multipoint nudeation model. Data from Ring [34],... 

Scores Plot (Sample Diagnostic) The Factor 2 versus Factor l plot is shown in Figure 5.119 with the points labeled by run order. The samples in this score space form multiple lines with similar slopes. Each line contains the spectra from a single standard (design point) at var ing temperatures. For example, samples 49-54 correspond to spectra collected from a single standard... 

Note that z is the deviation of a data point from the mean relative to one standard deviation. That is, when x — p = cr, zis equal to one when x — p = 2(t, z is equal to two and so forth. Since z is the deviation from the mean relative to the standard deviation, a plot of relative frequency versus z yields a single Gaussian curve that describes all populations of data regardless of standard deviation. Thus, Figure 6-4b is the normal error curve for both sets of data used to plot curves A and B in Figure 6-4a. 

A 0.5788-g sample of a purified organic acid was dissolved in water and titrated potentiometrically. A plot of the data revealed a single end point after 23.29 mL of 0.0994 M NaOH had been introduced. Calculate the molecular mass of the acid. 21-23. Calculate the potential of a silver indicator electrode versus the standard calomel electrode after... 

The equation accounts for 89% of the variance in the potency, and the standard error is at the level of the reported experimental error. DiPaolo showed that a plot of potency versus reveals nonlinear dependence with a maximum point. However, a quadratic form is not able to unite the data for all three classes of compounds into a single equation. It is the combination of the reciprocal of x together with Xp that gives a single equation for the three chemical classes. Examination of the equation indicates that the maximum occurs at X = 4.5 and Xp = 0.863, values near to those for butyl propionate and propyl butyrate. 

At OSI level 7 we measured FTP transfer rates versus nominal transfer rates configured in the access points for the IEEE 802.1 lb, g standards. Every measurement was the average for a single FTP transfer, using a binary file size of 100 Mbytes. The average results thus obtained are summarized in Table 15.1 and represented in Fig. 15.6 both for Expb and Expc. Polynomial fits to data were made for the implementation of each standard. It was found that, for each AP type, the best FTP performances are for 802.llg. APc shows, on average, a better FTP performance than APb, both for 802.11g and 802.1 lb. These results show the same trends found for TCP throughput. 

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