Grouping errors

Fig. 2 Effect of alkaline conditions on oxidized cotton linters. Left Changes in Mw (error bars 5%). Right Changes in carbonyl groups (error bars 2%)...

The compliance and commitment of taking the treatment agent is also very crucial for a snccessful clinical trial. Although pill counting has been successfully used as one criterion for compliance, serum levels of the test agent in the volunteers is obviously the most desired parameter to verify compliance. Low compliance compromises the chnical trials by reducing the power of the study and may offset the grouping errors. 

Ward s Method With the Ward method, the clusters are aggregated such that a minimum increase in the within-group error sum of squares results ... 

For machine tools, we group errors in error motions of spindles and rotary axes (e.g., axial error motion, radial error motion), error motions of linear axes (e.g., linear positioning error motion, straightness error motion, pitch error motion), contouring errors (e.g., circular error) (ISO 230-1 2012). Errors of machine tools may be also grouped according to the error source geometric errors, errors of the numerical control, dynamic errors, thermal errors, load errors, etc. 

DeShon, R. P. and Alexander, R. A. (1996], "Alternative procedures for testing regression slope homogeneity when group error variances are unequal," Psychological Methods, 1 (3], 261-77. 

Judgment had to be exercised in data selection. For each fluid, all available data were first fit simultaneously and second, in groups of authors. Data that were obviously very old, data that were obviously in error, and data that were inconsistent with the rest of the data, were removed. 

The model is predictive and uses a method of contributing groups to determine the parameters of interaction with water. It is generally used by simulation programs such as HYSIM or PR02. Nevertheless the accuracy of the model is limited and the average error is about 40%. Use the results with caution. 

In the case of Langmuir monolayers, film thickness and index of refraction have not been given much attention. While several groups have measured A versus a, [143-145], calculations by Knoll and co-workers [146] call into question the ability of ellipsometry to unambiguously determine thickness and refractive index of a Langmuir monolayer. A small error in the chosen index of refraction produces a large error in thickness. A new microscopic imaging technique described in section IV-3E uses ellipsometric contrast but does not require absolute determination of thickness and refractive index. Ellipsometry is routinely used to successfully characterize thin films on solid supports as described in Sections X-7, XI-2, and XV-7. 

Abstract. A smooth empirical potential is constructed for use in off-lattice protein folding studies. Our potential is a function of the amino acid labels and of the distances between the Ca atoms of a protein. The potential is a sum of smooth surface potential terms that model solvent interactions and of pair potentials that are functions of a distance, with a smooth cutoff at 12 Angstrom. Techniques include the use of a fully automatic and reliable estimator for smooth densities, of cluster analysis to group together amino acid pairs with similar distance distributions, and of quadratic progrmnming to find appropriate weights with which the various terms enter the total potential. For nine small test proteins, the new potential has local minima within 1.3-4.7A of the PDB geometry, with one exception that has an error of S.SA. 

The great advantage of WLN codes is their compactness. Both compactness and unambiguity are achieved only by a complex set of rules, which make the notation difficult to code and error-prone. Since much information had been stored in the WLN code (functional groups, fragments, etc.), much effort was spent in the devel-... 

The maximum number of latent variables is the smaller of the number of x values or the number of molecules. However, there is an optimum number of latent variables in the model beyond which the predictive ability of the model does not increase. A number of methods have been proposed to decide how many latent variables to use. One approach is to use a cross-validation method, which involves adding successive latent variables. Both leave-one-out and the group-based methods can be applied. As the number of latent variables increases, the cross-validated will first increase and then either reach a plateau or even decrease. Another parameter that can be used to choose the appropriate number of latent variables is the standard deviation of the error of the predictions, SpREss ... 

The F statistic, along with the z, t, and statistics, constitute the group that are thought of as fundamental statistics. Collectively they describe all the relationships that can exist between means and standard deviations. To perform an F test, we must first verify the randomness and independence of the errors. If erf = cr, then s ls2 will be distributed properly as the F statistic. If the calculated F is outside the confidence interval chosen for that statistic, then this is evidence that a F 2. 

Analytical methods may be divided into three groups based on the magnitude of their relative errorsd When an experimental result is within 1% of the correct result, the analytical method is highly accurate. Methods resulting in relative errors between 1% and 5% are moderately accurate, but methods of low accuracy produce relative errors greater than 5%. 

As a polymer prototype consider an n-alkane molecule consisting of n methylenes and 2 methyl groups. How serious an error is made in M for different n s if the difference in molecular weight between methyl and methylene groups is ignored ... 

Historically, the discovery of one effective herbicide has led quickly to the preparation and screening of a family of imitative chemicals (3). Herbicide developers have traditionally used combinations of experience, art-based approaches, and intuitive appHcations of classical stmcture—activity relationships to imitate, increase, or make more selective the activity of the parent compound. This trial-and-error process depends on the costs and availabiUties of appropriate starting materials, ease of synthesis of usually inactive intermediates, and alterations of parent compound chemical properties by stepwise addition of substituents that have been effective in the development of other pesticides, eg, halogens or substituted amino groups. The reason a particular imitative compound works is seldom understood, and other pesticidal appHcations are not readily predictable. Novices in this traditional, quite random, process requite several years of training and experience in order to function productively. 

Standard deviations from two to five or more. This means that the upper seventeenth percentile may be as much as from two to five times the mean. This variabihty is compounded by the problem of estimating the exposure of a group of workers having differing exposures to find the most exposed workers. Compared to this environmental variabihty, the variabihty introduced by the sampling and analytical error is smah, even for those methods such as asbestos counting, which are relatively imprecise. 

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