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Outliers removal

The 20% soy lecithin (Table 7.17) and the 2% DOPC (Table 7.15) intrinsic permeabilities may be compared in a Collander equation, as shown in Fig. 7.44. The slope of the regression line, soy versus DOPC, is greater than unity. This indicates that the soy membrane is more lipophilic than the DOPC membrane. Intrinsic permeabilities are generally higher in the soy system. Three molecules were significant outliers in the regression metoprolol, quinine, and piroxicam. Metoprolol and quinine are less permeable in the DOPC system than expected, based on their apparent relative lipophilicities and in vivo absorptions [593]. In contrast, piroxicam is more permeable in DOPC than expected based on its relative lipophilicity. With these outliers removed from the regression calculation, the statistics were impressive at r2 0.97. [Pg.215]

Figure 5. Sample semi-variogram for RSR with 7 "outliers" removed. Figure 5. Sample semi-variogram for RSR with 7 "outliers" removed.
It is evident that copper appears to be the major component in most of the coins of all emperors and titles. What becomes interesting is that lead is almost always the major component in the percent fraction of elements other than copper, even more so than tin. In Figures 1 - 3, for instance, it appears most prominently that even with the outliers removed, lead is present in greater amounts than tin. [Pg.242]

After removal of size from the data set (outliers removed previously), hierarchical and k-means cluster analyses fail to distinguish the two texture groups in the Chinautla-Sacojito data. Discriminant analysis with the size-corrected data yields nonsignificant test statistics for the effect of group (tempered vs. nontempered) and misclassifies 22 of 76 observations. [Pg.86]

A scatterplot of the results, with outliers, removed, showed three groups of pottery based on their elemental composition (Fig. 8.13). The values used on the X- and T-axes of the scatterplot are based on principle components, a technique to create summary statistics that combine the results from all of the elements used in the study. Each data point on the graph represents a sherd sample from Pinson Mounds. Thus, the X- and T-axes use most of the results of the NAA measurements. The authors of the study then drew ovals around clusters of data points in the graph to distinguish three compositional groups. These ovals should encompass 90% of the data points in the group. These compositional groups should represent pottery... [Pg.231]

Figure 3.3 Rankit plots for results of the RACI titration competition (a) All data (b) with extreme outlier at 0.9083 M removed (c) with seven outliers removed. Note the shrinking x-axis range. Figure 3.3 Rankit plots for results of the RACI titration competition (a) All data (b) with extreme outlier at 0.9083 M removed (c) with seven outliers removed. Note the shrinking x-axis range.
Looking at the final plot in figure 3.3(c) with all outliers removed, one can see it is a good straight line. Although it is possible to quantify how well the data are normally distributed, such calculations are not simple. Your ability to determine linearity by eye is actually very reliable and because of its simplicity this is the method most commonly used. The question of how we can statistically justify removing such outliers is the subject of the next section. [Pg.77]

Parameter All data Outliers removed No outliers and no influential observations... [Pg.328]

Occasionally, naive samples are encountered with preexisting or high levels of ADAs. If a confirmatory test shows that the ADA response is specific to the drug, such samples should be excluded from the cut point calculations. In addition, samples that are identified as outliers using appropriate statistical criteria [34] should also be excluded or down weighted in the analyses. If a substantial number of naive samples are positive from the relevant disease population, it is acceptable to include samples from a healthy or non-diseased population for determining the cut point. For example, if the distribution of the data of outlier-removed samples is not statistically different between healthy and disease-matched subjects (i.e., means and variances are not significantly different), then the cut point evaluation can be made from a collection of samples where half the samples are from healthy subjects and the other half are from the relevant disease population. [Pg.207]

Fig. 4.4. Histogram of C(aromatic) - CN bond lengths after outlier removal... Fig. 4.4. Histogram of C(aromatic) - CN bond lengths after outlier removal...
Fig. A.2. Effects of outlier removal and subdivision based on coordination number and oxidation state for the Cu-Cl bond, (a) All data (b) all data without outliers [>4a (sample) from mean] (c) all data for which Cu is four coordinate Cu". Relevant statistics (see text) are ... Fig. A.2. Effects of outlier removal and subdivision based on coordination number and oxidation state for the Cu-Cl bond, (a) All data (b) all data without outliers [>4a (sample) from mean] (c) all data for which Cu is four coordinate Cu". Relevant statistics (see text) are ...
The Inslde-shoe pads ranged In exposure from 1.6 to 3.1 pg In the application to corn. The exposure was 0.9 to 3.3 pg (outliers removed) In compressed gas spraying and 4.0 to 4.9 In dusting when applying to beans. This compares to shoe exposures of 32 to 41 pg for corn and 28 to 66 for beans. [Pg.155]

Constituent No Outliers Removed Outliers (no. in parenthesis) Removed... [Pg.261]

All data Outlier removed Four of six parameters out Fine-tuned... [Pg.302]


See other pages where Outliers removal is mentioned: [Pg.221]    [Pg.117]    [Pg.281]    [Pg.282]    [Pg.215]    [Pg.86]    [Pg.518]    [Pg.9]    [Pg.148]    [Pg.213]    [Pg.143]    [Pg.52]    [Pg.323]    [Pg.190]    [Pg.89]    [Pg.61]    [Pg.486]    [Pg.487]    [Pg.37]    [Pg.268]   
See also in sourсe #XX -- [ Pg.757 ]




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