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** Average Boltzmann factor in a random **

Two-way analysis of variance End-point strength Fixed factors(s) Force, Punch Random factor(s) [Pg.162]

Intermolecular forces are attractive or repulsive forces between atoms, molecules, and/or ions. The attractive forces compete with the randomizing factor of kinetic energy. The structure that a particular substance exhibits depends on the [Pg.158]

Midlife or premature failures roughly constant failure rate due to random factors [Pg.210]

As we see in Chapter 2, the normal distribution comes about when a large number of purely random factors is responsible for the distribution. It is mainly applicable to particles [Pg.635]

We see that there is a much greater energy rise when a mole of I2 dissolves in CCU than when a mole of I2 dissolves in alcohol. Thus the energy factor (favoring the crystal) that opposes the randomness factor (favoring solution) is much [Pg.166]

When the investigated process shows a small residual variance we can consider that the variance results from the action of small random factors. At the same time, this small variance is a good indication of an excellent reproducibility of the experimental measurements. Conversely, a great residual variance can show that the measurements are characterized by poor reproducibility. However, this situation can also result from one or more unexpected or unconsidered factors this situation can be encountered when the interactions between the factors (parameters) have been neglected. In these cases, the variance of the interactions represents an important part of the overall residual variance. [Pg.421]

An exploratory analysis was performed using a four-factor ANOVA model, with treatment, period, and sequence as fixed factors and subject within sequence as random factor. The results from the ANOVA were used to calculate the back-transformed 90 % confidence intervals (Cl) for the differences between the fed and fasted condition in the log-transformed exposure measurements (Cmax, AUCo-t and AUCo-cc). For Cmax the difference between fasting and fed conditions was found to be statistically significant while this was not the case for the AUC parameters. [Pg.670]

Besides, after identifying the effects, it is necessary to compare variances of the process produced by the variation of the factors and the variances of the process produced by the random factors [5.5, 5.8, 5.29-5.31]. [Pg.414]

The root nodes of each tree structure are connected, corresponding to each variable under consideration. In each single tree, the deterministic trend information and the random factors are all accounted for. The rationale behind using the multivariate tree structure is to be able to capture the correlations among variables. Here, the connection among variables is arbitrary, and the apparent parent-child connection does not really imply the parent-child dependence, but it is just a way to model the relation be- [Pg.159]

Radioactivity The ability possessed by some natural and synthetic isotopes to undergo nuclear transformation to other isotopes, 513 applications, 516-518 biological effects, 528-529 bombardment reactions, 514-516 diagnostic uses, 516t discovery of, 517 modes of decay, 513-514 nuclear stability and, 29-30 rate of decay, 518-520,531q Radium, 521-522 Radon, 528 Ramsay, William, 190 Random polymer 613-614 Randomness factor, 452-453 Raoult s law A relation between the vapor pressure (P) of a component of a solution and that of the pure component (P°) at the same temperature P — XP°, where X is the mole fraction, 268 [Pg.695]

The final costs are highly dependent upon site-specific conditions. Contributing factors to the final cost include the waste characteristics, including its physical form and chemical makeup the amount of pretreatment required transportation of raw materials to the site and treated materials from the site and other random factors such as health and safety requirements and regulatory factors (D150141, p. 7.100). [Pg.447]

Precision is a measure of how variable a method is in its measurement of a product parameter under normal usage. In statistical terms, precision is measured by the variance of the method. Additionally, the typical sources of variability are accounted for in assessing precision these are random factors external to the method, such as analysts, days, and changing assay hardware [Pg.15]

The example presented above successfully illustrates hotv we develop and use the EVOP method for a discontinuous process. When we have a continuous process, it is suggested to transform it artificially into a discontinuous process. For this purpose, we must take into consideration all the factors of the process representing flow rates according to a fixed period of time. With these transformations we can control the effect of the random factors that influence the continuous process. If, for example, we consider the case of a continuous reactor, then, the conversion can be obtained from the analysis of 5 to 6 samples (each selected at a fixed period of time), when the corresponding input and output quantities are related to the [Pg.413]

** Average Boltzmann factor in a random **

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