Marking data points

O Mark Data Points PI Display Evaluation B Display Statistics PI highlight Error States... 

Mark Data Points 0 Display Evaluation ES Display Statistics 0 Highlight Error States... 

We notice that the individual data points are not displayed. To mark the points, click the LEFT mouse button on the text Mark Data Points. The square next to the text Mark Data Points should fill with a checkmark El, indicating that the option is enabled ... 

Before continuing, you should disable the Mark Data Points option. In the future, if you display a trace with thousands of points, the trace will be cluttered with little data point markers. 

Set range to use all of the graph page label axes and clearly mark data points. 

FiG. 10 Normalized density profiles p z)/for the associating fluid at a hard wall. The association energy is jk T — 7 and the bulk density is p = 0.2098 (a), e ykgT = 5 and the bulk density equals 0.9038 (b). The solid and dashed lines denote the results of the modified Meister-Kroll theory and the theory of Segura et al., respectively. The Monte Carlo data in (a) are marked as points. (From Ref. 145.)... 

Figure 4.12 (left). The hardness data is grouped by stamp, (right). By subtracting the weight-dependent portion of the hardness, the residuals are seen to cluster much more closely, particularly for those stamps marked with arrows. Because of the limited hardness resolution (0.1 kg), the symbols for two or more data points can overlap. The vertical bar indicates sfj. 

Figure 4.51. Distribution of experimental data. Six experimental formulations (strengths 1, 2, resp. 3 for formulations A, respectively B) were tested for cumulative release at five sampling times (10, 20, 30, 45, respectively 60 min.). Twelve tablets of each formulation were tested, for a total of 347 measurements (13 data points were lost to equipment malfunction and handling errors). The group means were normalized to 100% and the distribution of all points was calculated (bin width 0.5%, her depicted as a trace). The central portion is well represented by a combination of two Gaussian distributions centered on = 100, one that represents the majority of points, see Fig. 4.52, and another that is essentially due to the 10-minute data for formulation B. The data point marked with an arrow and the asymmetry must be ignored if a reasonable model is to be fit. There is room for some variation of the coefficients, as is demonstrated by the two representative curves (gray coefficients in parentheses, h = peak height, s = SD), that all yield very similar GOF-figures. (See Table 3.4.)...

Fig. 2.6.4 Sensitivity comparison between direct (a) and remote detection (b). With direct detection, an FID is recorded transiently with M data points, which are marked with the symbols x in the first FID in (a). Remotely, M encoding steps are necessary to obtain the same data set, which allows one to perform M signal averaging steps in the direct dimension in the same time. The encoding and detection steps in the remote experiment are intermingled, therefore only a time overhead correspon-...

Strong data point to a dramatic shift of pesticide dietary risks from fresh fruits and vegetables grown in the US to those imported from abroad. As a nation, we have more work to do, and contentious decisions ahead if we are to markedly reduce pesticide dietary risks. 

The absorbance spectrum in Figure 54-1 is made from synthetic data, but mimics the behavior of real data in that both are represented by data points collected at discrete and (usually) uniform intervals. Therefore the calculation of a derivative from actual data is really the computation of finite differences, usually between adjacent data points. We will now remove the quotation marks from around the term, and simply call all the finite-difference approximations a derivative. As we shall see, however, often data points that are more widely spread are used. If the data points are sufficiently close together, then the approximation to the true derivative can be quite good. Nevertheless, a true derivative can never be measured when real data is involved. 

Fig. 10. Dependence of the exponent a of Mark-Houwink equation on the 1,4-DVB content of the microgels formed in emulsion. The data points were calculated from the [x ] and Rvalues reported by Hoffmann ( ) [70] and by Bolle (A) [83].

Fig. 3.8. Profiles of interstellar absorption lines observed in the line of sight to the star HD 93521 with the Goddard high resolution spectrograph at the Hubble Space Telescope. Solid lines are theoretical profiles based on cloud velocities indicated by the tick marks at the top dots indicate the data points. After Spitzer and Fitzpatrick (1993). Courtesy Ed Fitzpatrick.

Some ridge sections are underlain by mantle melt anomalies, or hot spots, such as at the Azores and Galapagos Islands. These are marked by the stars in Figure 19.1 and data points 12 and 13 in Figure 19.5. Mantle upwelhng beneath both these ridge sections has abnormally thickened the oceanic crust to at least about 10 km. Most of the 47 known hot spots lie more than 500 km from a ridge axis. The Hawaiian islands are a notable example. 

Figure 12 shows the classical method of obtaining the Mark-Houwink coefficients, K and a, by plotting the log [n](v) vs. log M(v) for this polymer in THF at 50°C. The data points used for the plot in Figure 12 are indicated by the area between the arrows in Figure 10. Linear regression analysis of the data resulted in K o =1.86x10" and a o =0.662 with a correlation coefficient or t =u.9996 for NBS 70o polystyrene.

Non-linear Hydrodynamic Volume Calibration Curve. The hydrodynamic calibration curve, log. V shown in Figure lb, is generated using the commercially available narrow MWD polystyrene standards listed in Table 1 and published values (28, 29) of the Mark-Houjjink parameters K and a for polystyrene in THF a 25°C, (K=1.6 x 10, o = 0.706 for > 10,000 and K = 9.0 x 10, a = 0.5 for Mw <10,000). The experimental data points composing the non-linear calibration curve were fitted with the phenomenologically based Yau-Malone equation.(30) This equation is derived from diffusion theory and is expressed as follows ... 

Important note By clicking the OK button, you will change the settings for all future plots. All plots In this session as well as plots In the future will mark the data points. If you do not want to make a setting permanent, you must change the setting back before you exit Probe... 

We can now see small marks on the trace that indicate the locations of the data points. This plot shows us that the rise time of the circuit is a linear function of the collector resistor value. 

Fig. 10 Maximum 2PA cross section as a function of transition dipole moment Mge for D-tt-D diphenylpolyenes (open circles) and D-tt-D distyrylbenzenes (filled circles). Data from [94,97]. Data points for the molecules in Tables 1 and 2 are marked by the corresponding acronym...

Values of B calculated from the ordinate intercepts are shown in Fig. 23 as a plot of B/(2q)3 against the number of the Kuhn segments N. For N<4, the data points for the indicated systems almost fall on the solid curve which is calculated by Eq. (78) along with Eqs. (43), (51), (52), and Cr = 0. A few points around N 1 slightly deviate downward from the curve. Marked deviations of data points from the dotted lines for the thin rod limit, obtained from Eq. (78) with Le = L and de = 0, are due to chain flexibility the effect is appreciable even at N as small as 0.5. The good lit of the solid curve to the data points (at N 4) proves that the effect of chain flexibility on r 0 has been properly taken into account by the fuzzy cylinder model. 

By defined Points lets you mark certain data points as being on the baseline. From these points a baseline is then calculated according to the specified baseline function, which may (and should) be inspected before the correction is applied. 

The uppermost line of Figure 13.37(a) marks the onset of flooding which is the point at which sharp increase of pressure drop obtains on a plot against liquid rate. Flooding limits also are represented on Figure 13.36 in practice, it is customary to operate at a gas rate that is 70% of that given by the line, although there are many data points below this limit in this correlation. 

When a value of r = 0.78 is used, the data points for MSM copolymers (shown as crosses) coincide with the curve for polystyrene. According to Equation 4, r may be calculated from the coefficient K for homopolymers. When applied to the data on polystyrene and poly (methyl methacrylate) (3), a value of 0.72 is obtained, in good agreement with the above value of 0.78. The slight difference is probably the result of the polydispersity in the copolymers since the Mark-Houwink equation requires monodispersed polymers. 

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