Error relative importance

Although checklists are a useful way of transferring information about human-machine interaction to designers and engineers, they are not a standalone tool and they cannot provide a substitute for a systematic design process. The main concern with checklists is that they do not offer any guidance about the relative importance of various items that do not comply with the recommendations, and the likely consequences of a failure due to a noncompliance. To overcome such problems, checklists should be used in combination with other methods of task analysis or error analysis that can identify the complexities of a task, the relationships among various job components, and the required skills to perform the task. 

On the other hand, MCCC considers the influence of the variation of one parameter on model output in the context of simultaneous variations of all other parameters. In this situation, is smaller than 1 in absolute value and its size depends on the relative importance of the variation of model output due to the parameter of interest and the variation of model output given by the sum total of all sources (namely, the variability in all structural parameter values plus the error variance). 

With the triples correction added, the error relative to experiment is still as large as 15 kJ/mol. More importantly, we are now above experiment and it is reasonable to assume that the inclusion of higher-order excitations (in particular quadruples) would increase this discrepancy even further, perhaps by a few kJ/mol (judging from the differences between the doubles and triples corrections). Extending the coupled-cluster expansion to infinite order, we would eventually reach the exact solution to the nonrelativistic clamped-nuclei electronic Schrodinger equation, with an error of a little more than 15 kJ/mol. Clearly, for agreement with experiment, we must also take into account the effects of nuclear motion and relativity. 

Finally, while total promotion expenditures over all types of promotional efforts approximately doubled between 1996 and 2001 (Table 9.1), so too did revenues, and thus total promotional intensity remained relatively constant. The total promotion-to-sales dollar ratio has hovered between 14% and 16% between 1996 and 2002, but it appears to have increased tol7.1% in 2003. This most recent increase may reflect the rising relative importance of free samples provided physicians, which in large part (Table 9.1), as noted above, are evaluated at their full retail prices rather than at marginal production costs. The apparent increases might also simply reflect the effects ofvarious measurement errors. 

The ALLOC method with Kernel probability functions has a feature selection procedure based on prediction rates. This selection method has been used for miik >s5) and wine > data, and it has been compared with feature selection by SELECT and SLDA. Coomans et al. suggested the use of the loss matrix for a better evaluation of the relative importance of prediction errors. 

An important consideration is the relative importance of the water and the diet as a source of chemical uptake in the organism. Equation (30) illustrates that, to a large degree, the relative concentrations of the chemical substance in the water and the diet of the organism control the BAF. In laboratory experiments where bioaccumulation factors are measured, it is therefore important to choose appropriate concentrations CWD and CD, because they affect conclusions drawn about the relative importance of the diet and water as routes of chemical intake. Under field conditions, the bioaccumulation factors in organisms can vary, depending on the relationship between the chemical concentrations in the water and the diet, especially if the chemical is very hydrophobic (log Kow > 5). If the BAF measured in one ecosystem is used to assess the BAF in another ecosystem, an error could be made if this diet/ water concentration relationship or values of kD vary between the ecosystems. 

The sensitivity of this procedure to errors in the predicted yields of Table IV was checked. An overestimation of all three (C8H16, C9H18> and C10H2o) yields from the prediction would have no effect on the estimated retro-ene contribution, and any changes in the free radical path contributions would be equal and opposite and proportional to the size of the error in prediction. An error in decene alone would affect all three. For example, a 10% overestimate of decene in Table IV changes the relative importances of the retro-ene, abstraction, and addition paths by + 0.004 ( 3.5% ), — 0.05 (10% ), and -f 0.05 (10% ), respectively. Thus, the predicted contribution of the retro-ene path is relatively insensitive to errors in the Rice-Kossiakoffff predictions. 

The primary technical limitation on the accuracy of molecular weights so determined is the sedimentation constant. Since the molecular weight is directly proportional to the sedimentation constant, where S is low, small errors in S will be relatively important. For -dextrin with S = 0.47, if S is in error by only 0.02 (an average error for measurements of this sort) this will give an error of 50 in the molecular weight. A second essential factor which so far has not been determined with high precision is the partial specific volume of the carbohydrate. Nevertheless, it has been possible to obtain molecular weights which are within a few perct nt of the theoretical values (see Table IV). 

This comprehensive study also tested the relative importance of the various terms in Eq. (18), and its relative performance when compared with modified Karplus equations of the Pachler, Haasnoot, and Colucci el al. types. Based on standard deviations of errors, the ranking of the four most important terms was found to be cos 2ip, cos

important term is the combined electronegativity/electronegativity orientation term, and the fourth most significant one is the bond angle term, the first- and third-ranked terms... 

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