Scatter graphs

It can thus be seen that most of the variation in the data (85.9%) is explained by the fir principal component, with all but a fraction being explained by the first two componeni These two principal components can be plotted as a scatter graph, as shown in Figu 9.33, suggesting that there does indeed seem to be some clustering of the conformatioi of the five-membered ring in this particular data set. 

The derivation outlined may thus serve to explain such scattered graphs however, no possibility is offered of estimating pi and 2- The situation is complicated by the known fact that the plot of AH versus AS is statistically erroneous. The same objections apply to Leffler s special case (153) when experimental error is formally treated as an additional interaction mechanism with P2 - Texp Even in this case, no possibility is given of estimating the real Pi. 

Measure of the closeness of fit of a scatter graph to its regression line where r2 = 1 is a perfect fit. Volume 1(6). 

Figure 7 Two-dimensional scatter graph of area/depth2 plotted against A for a variety of cytochrome P450 substrates. The curve marks the distinction between P450 I substrates and P450 11 substrates where the latter lie below the line.

Use the list of stmcture types to work out the coordination number of the lanthanide for each compound. Plot a scatter graph of Average coordination number (y axis) against Atomic number (x axis) and comment. 

Figure 24.4 Plot of the DSC trace (solid line) and conductivity (scatter graph) as a function of temperature for tetramethyleimmonium dicyanamide. The changes in conductivity with temperature mirror the thermal transitions, with an increase up to phase III and a dramatic increase on melting. As the temperature increases, there is a greater internal motion within the material and consequently the conductivity increases.

Scatter graphs best show possible relationships between two variables. The purpose of the graph is to try to decide if some partial or indirect relationship—a correlation—exists. 

Plot z-score against the data on a scatter graph. 

The residual values, y, — y, = e, plotted against the fitted values, %. This residual scatter graph is useful in ... 

Because of this, scatter graphs do not have descriptors in the same sense as other graphs. 

From a small-angle scattering graph of a sample of agglomerates derive the dimensions of the agglomerates and the surfaces of the powder particles. 

Risk estimation refers to putting the frequency and consequence components together, either through a formula such as Risk = frequency X consequence, or by placing the hazardous event on a scatter graph or matrix of frequency versus consequence. 

We analyzed the relationship between Pr and stiffness on the basis of dF. We plotted dF-Pr and stiffness-dF scatter graphs using the data set obtained from the six patients. The averaged dF-Pr scatter graph for the six subjects is shown in Fig. 3. It approximated a high linear correlation in the loaded state whereas a nonlinear correlation in the unloaded state. In contrast, the averaged stiffness-dF scatter graph for the six subjects (Fig. 4) approximated a nonlinear exponential correlation in the loaded state whereas a linear correlation in the unloaded state. 

Because the averaged Dp-Pr scatter graph for the six subjects exhibits a linear correlation under loaded conditions, we assumed elasticity varied linearly. We calculated the shear modulus (G) on the basis of Lee and Radok s correspondence principle [16]. The value of G was convergent to 1.94 0.49 kPa in the shear modulus-depth graph. 

The scatter graph of dF-Pr shows a linear correlation between dF and Pr in the loaded state (Fig. 3). Therefore, the Pr-value was approximated by the dF-value as Pr = 0.853dF + 2.729. On the other hand, in the unloaded state, it shows a nonlinear correlation and the dF value still continued to exhibit a frequency change of 40 Hz at the release point, that is, when the probe pressure against the object was zero. In this context, the contact area, surface conditions, and bulk flow of water content were considered relevant [17,18]. 

Due to its spreadsheet approach, ProjectLeader inherently organizes the data. Additional tools that make it a complete research-project management package are at present included only in the Macintosh version, and include full tracking and annotation mechanisms, the possibility to produce scatter graphs, and the integration of data tables, graphs, and documentation. 

Another way of getting the coefficients for a limited number of fitting functions is to use X-Y scatter graphs in Excel and add a trendline. 

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