Bias significant

Sample Reference Value, ppm Measured Value, ppm Bias, ppm Bias significance... 

The main difference between the force-bias and the smart Monte Carlo methods is that the latter does not impose any limit on the displacement that m atom may undergo. The displacement in the force-bias method is limited to a cube of the appropriate size centred on the atom. However, in practice the two methods are very similar and there is often little to choose between them. In suitable cases they can be much more efficient at covering phase space and are better able to avoid bottlenecks in phase space than the conventional Metropolis Monte Carlo algorithm. The methods significantly enhance the acceptance rate of trial moves, thereby enabling Icirger moves to be made as well as simultaneous moves of more than one particle. However, the need to calculate the forces makes the methods much more elaborate, and comparable in complexity to molecular dynamics. 

Analytical chemists make a distinction between error and uncertainty Error is the difference between a single measurement or result and its true value. In other words, error is a measure of bias. As discussed earlier, error can be divided into determinate and indeterminate sources. Although we can correct for determinate error, the indeterminate portion of the error remains. Statistical significance testing, which is discussed later in this chapter, provides a way to determine whether a bias resulting from determinate error might be present. 

Because the technical barriers previously outhned increase uncertainty in the data, plant-performance analysts must approach the data analysis with an unprejudiced eye. Significant technical judgment is required to evaluate each measurement and its uncertainty with respec t to the intended purpose, the model development, and the conclusions. If there is any bias on the analysts part, it is likely that this bias will be built into the subsequent model and parameter estimates. Since engineers rely upon the model to extrapolate from current operation, the bias can be amplified and lead to decisions that are inaccurate, unwarranted, and potentially dangerous. 

The bias does not have significant impact on the measurement adjustment... 

The bias does not contribute significantly to the errors in the constraints... 

However, other bias errors are so substantial that their presence will significantly distort any conclusions drawn from the adjusted measurements. Rectification is the detection of the presence of significant bias in a set of measurements, the isolation of the specific measurements containing bias, and the removal of those measurements from subsequent reconcihation and interpretation. Significant bias in measurements is defined as gross error in the literature. 

To bias the sampling toward a region of interest that would not otherwise be significantly populated, a restraining potential UXq) is added to the potential energy of the system. U, is often referred to as an umbrella potential [37]. For concreteness, we assume the harmonic form... 

Representativeness can be examined from two aspects statistical and deterministic. Any statistical test of representativeness is lacking becau.se many histories are needed for statistical significance. In the absence of this, PSAs use statistical methods to synthesize data to represent the equipment, operation, and maintenance. How well this represents the plant being modeled is not known. Deterministic representativeness can be answered by full-scale tests on like equipment. Such is the responsibility of the NSSS vendor, but for economic reasons, recourse to simplillcd and scaled models is often necessary. System success criteria for a PSA may be taken from the FSAR which may have a conservative bias for licensing. Realism is more expensive than conservatism. 

Recent work with multi-layer polymer LEDs has achieved impressive results and highlights the importance of multi-layer structures [46]. Single-layer, two-layer and three-layer devices were fabricated using a soluble PPV-based polymer as the luminescent layer. The external quantum efficiencies of the single-layer, two-layer, and three-layer devices were 0.08%, 0.55%, and 1%, respectively, with luminous efficiencies of about 0.5 hn/W, 3 lm/W, and 6 lm/W. These results clearly demonstrate improvement in the recombination current because of the increase in quantum efficiency. The corresponding increase in luminous efficiency demonstrates that the improvement in recombination efficiency was achieved without a significant increase in the operating bias. 

Had the calculated value for t been less than 1.80 then there would have been no significance in the results and no apparent bias in the laboratory procedure, as the tables would have indicated a probability of greater than 1 in 10 of obtaining that value. It should be pointed out that these values refer to what is known as a double-sided, or two-tailed, distribution because it concerns probabilities of values both less and greater than the mean. In some calculations an analyst may only be interested in one of these two cases, and under these conditions the -test becomes single-tailed so that the probability from the tables is halved. 

It is probably fair to say that the academic studies conducted on the differences between formal and informal mentoring have an American bias. You might not perceive this as a big deal, but when you think back to the section in Chapter 1 regarding the different concepts of mentoring in America and Europe, you will appreciate the significance. Just to remind you, the American view of mentoring emphasizes protection and sponsorship, whilst the European view favours the mentee s insight and... 

NXHOMO of the hydroxy-substituted dihydroanthracene is also symmetric in sign. Therefore, the antisymmetric orbital does not interact significantly with these vacant n orbitals of 36, resulting in an unperturbed n face of the carbonyl it orbital. This motif is regarded as an example of orbital non-interaction [105], Thus, the reduction of 2-methoxy and 3-methoxydibenzobicyclo[2.2.2]octadienones (34c and 34f) should intrinsically show little or no bias. 

Each of the analyses reported outcomes for patients responding to and continuing treatment after the original 6-week clinical trial that is, after the exclusion of patients withdrawing from the original trial for whatever reason (e.g. poor tolerability, lack of response). This probably introduced bias in favour of haloperidol, since there were significantly more responders to olanzapine. 

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