Once the form of the correlation is selected, the values of the constants in the equation must be determined so that the differences between calculated and observed values are within the range of assumed experimental error for the original data. However, when there is some scatter in a plot of the data, the best line that can be drawn representing the data must be determined. If it is assumed that all experimental errors (s) are in thejy values and the X values are known exacdy, the least-squares technique may be appHed. In this method the constants of the best line are those that minimise the sum of the squares of the residuals, ie, the difference, a, between the observed values,jy, and the calculated values, Y. In general, this sum of the squares of the residuals, R, is represented by... [Pg.244]

The summary at the bottom of Table 5 indicates the relative agreement between the calculated data and that experimentally determined for this particular producer gas. It is suggested that the difference between calculated and determined data in this case may be due more to inaccuracies in the analysis of the produeer gas (particularly for methane) than to the fault of the mixture rule formula. This points up the fact that reliable gas analyses also are a necessary part of the calculated flammability limit data. [Pg.294]

Borisova et al. A diffuse-layer minimum was found in the C, E curves, but the capacitance dispersion was appreciable and the value of C at Emib for Cd was higher than that calculated using the C, E curve for Hg 10,220,221 jt was notect10 that one of the reasons for this was the roughness of the pc-Cd surface. Therefore, Cd, Pb, and T1 electrodes were remelted in an inert atmosphere to give solidified drop electrodes. The capacitance dispersion was somewhat lower, but the difference between calculated and experimental capacitance was still substantial.221... [Pg.103]

The largest differences between calculated and observed values are shown by naphthalene and anthracene. I feel confident that the differences are due to errors in the reported experimental values, especially since good agreement between experiment and theory is found for phenanthrene. [Pg.750]

These results can then be compared to experimental values (at the same temperature) in a number of informative ways. First we can plot the calculated values as a function of temperature and represent results as a line, see Figure 4. The experimental results can be represented as an error band vs temperature plot. Real differences are readily apparent since they must lie outside the 95% confidence limits. Another way to represent the difference is to plot the difference between calculated and experimental values as a function of temperature. In the same graph an estimate and plot of the experimental errors can also be made, see Figure 5. [Pg.84]

The termination criterion states that all absolute differences between calculated and actual total concentrations need to be smaller than 1015M. This provides sufficient numerical accuracy for many chemical problems at typical total concentrations around 103M. It is quite obvious that the computations become less accurate if the total concentrations get closer to the break criterion. We use an absolute termination criterion to allow for zero total component concentration. [Pg.56]

Structure determination from X-ray and neutron diffraction data is a standard procedure. Starting with a rough model, the accurate structure is determined using a least-squares structure refinement, which is based on kinematic diffraction and in which the differences between calculated and experimental intensities are minimized. X-ray and neutron diffraction are not applicable to all crystals. To determine crystal structures of thin layers on a substrate or small precipitates in a matrix (see figure 1) only electron diffraction (ED) can lead you to the crystal structure. [Pg.355]

Using databases or tables of SCS to predict proton chemical shifts, only through-bond effects are effectively considered, and a typical r.m.s. difference between calculated and experimental shifts is 0.3 ppm. This is a lower value than for shifts, but this is a much higher proportion of the chemical shift range (3 vs. 0.75%). [Pg.231]

The isotherm parameters are changed to minimize the squares of the differences between calculated and experimental profiles. [Pg.301]

Oxidation of the dihydroanthracene (50 mmoles) by oxygen at 4 atm. consumed 1.80 molecular equivalents (90 mmoles) of oxygen. This amount of oxygen corresponds to an 87% conversion to anthraquinone and a 13% conversion to anthracene. Analysis of the product gave corresponding values of 90 and 10%. The difference between calculated and experimental conversions may well be within experimental error. [Pg.224]

Model Hartree-Fock calculations which include only the electrostatic interaction in terms of the Slater integrals F0, F2, F and F6, and the spin-orbit interaction , result in differences between calculated and experimentally observed levels596 which can be more than 500 cm-1 even for the f2 ion Pr3. However, inclusion of configuration interaction terms, either two-particle or three-particle, considerably improves the correlations.597,598 In this way, an ion such as Nd3+ can be described in terms of 18 parameters (including crystal field... [Pg.1105]

Figure 15. Difference between calculated and experimental potentials for first excited 2 states of Hej molecule. Within experimental error the two curves are identical for r >3 A. |

Finally, Table 5 shows statistics grouped by structure. For all of the structures, a root-mean-square difference between calculated and observed structural shifts of 0.25 to 0.35 ppm is found. Also shown are the slope and intercept of the best-fit line and the linear correlation coefficient for various portions of the total database. Statistics for all structures are not significantly different than those for the B-form DNA duplexes alone. Again, the best results are obtained for base protons and for the HI position on the sugar. [Pg.202]

The difference between calculated and experimentally determined distributions is generally not larger than 5%. While this accuracy might not be great, clearly it is reasonable in the light of the approximations discussed above. More importantly, the error limit of ca. 5% seems to be general[31 33], i. e., the method is reliable. Two additional factors emerge from Table 7.2 ... [Pg.71]

The following table lists answers for all parts. Literature values are interpolated from tables in Perry s Chemical Engineers Handbook, 6th ed. The last column shows the percent difference between calculated and literature values at 0.85Tc. These range from 0.1 to 27%. For the normal boiling point (Tn), Psat should be 1.013 bar. Tabulated results for Psat do not agree well with this value. Differences range from 3 to > 100%. [Pg.561]

Calculated dissociation energies do not reflect ionic contributions and invariably map into the covalent crescent. Ionic percentages are therefore estimated directly as the difference between calculated and observed dissociation energies. [Pg.176]

standard deviation is an indicator for the average deviation of the regression line from the experimental points. For example, with one of the ethylene dibromide funs the average for the absolute values of differences between calculated and observed values of log P was 0.0053, and the standard deviation was 0.0079. [Pg.53]

So the additive functions must be discovered the values of the atom group contributions or increments must be derived. This derivation of group contributions is relatively easy when the shape of the additive function is known and if sufficient experimental data for a fairly large number of substances are known. The derivation is mostly based on trial and error methods or linear programming in the latter case the program contains the desired group increments as adjustable parameters. The objective function aims at minimum differences between calculated and experimental molar quantities. [Pg.62]

ORD were relatively minor when considering typical differences between calculated and experimental ORD such as seen in Fig. 4. [Pg.27]

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