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Data: evaluation

In the following pages further statistical methods of evaluation are set out, which permit temporal and spatial fluctuations of substances contained in water to be described and analyzed. [Pg.718]

In contrast to chemical analysis, in which standardization is already well advanced, statistical methods used for evaluating water quality data are, with few exceptions, not standardized but mostly a matter of tradition. The basis of all statistical evaluations should be an investigation plan which encompasses formulation of problems, data acquisition and an evaluation strategy. When drawing up plans for random sampling, all information which is already available about possible fluctuations of the system under examination should be taken into account. [Pg.718]

The requirement for statistical independence demands that two areas of data evaluation be kept separate from each other. [Pg.718]

In the first case the total volume of the sample under examination can be [Pg.718]

on the other hand, various time-dependent and/or location-dependent data are collected, the task of describing the population represented by these data can be more problematical. With surface water all substances contained can be defined as belonging to the parent population, but the [Pg.719]


A-scans with a visual evaluation by the tester to be of little significance. New measuring-data-evaluation-procedures were needed to place additional information at the testers disposal. [Pg.752]

Nuclear Data Sheets, Academic Press, San Diego, Calif., TvaluatedNuclear Structure Data File (ENSDF), a computer database of nuclear stmcture data evaluated by an international network of evaluators, is maintained at the National Nuclear Data Center, Brookhaven National Laboratory. NUDNTis a computer database of decay data extracted from the ENSDF. [Pg.459]

Complete automation with computer control and on-line data evaluation and reduction is also possible (Dean and Angelo 1971, Gregory and Young 1979, Larmon et al 1981.)... [Pg.52]

Modem communication for data evaluation by specialists at remote locations. [Pg.202]

The old maxim if it ain t broke don t fix it is very applicable in today s machinery. A study conducted at a major nuclear power facility found that 35% of the failures occurred after a major turnaround. This is why total condition monitoring is necessary in any performance based total productive maintenance system and leads to overhauls being planned on proper data evaluation of the machinery rather than on a fixed interval. [Pg.741]

If casing limitations are fixed by user-supplied relief valves, this information should be conveyed to keep the vendor from rating the compressors on other data. Evaluations can be more of a problem if the same design basis isn t universal with all vendors. Startup and shutdown consideration influence various components, shaft end seals, seal system pressures, and even thrust bearings in some instances. The use of an alternate startup gas, or the desire to operate a gas compressor on air to aid in plant piping dryout should be covered. [Pg.445]

State-of-the-art for data evaluation of complex depth profile is the use of factor analysis. The acquired data can be compiled in a two-dimensional data matrix in a manner that the n intensity values N(E) or, in the derivative mode dN( )/d , respectively, of a spectrum recorded in the ith of a total of m sputter cycles are written in the ith column of the data matrix D. For the purpose of factor analysis, it now becomes necessary that the (n X m)-dimensional data matrix D can be expressed as a product of two matrices, i. e. the (n x k)-dimensional spectrum matrix R and the (k x m)-dimensional concentration matrix C, in which R in k columns contains the spectra of k components, and C in k rows contains the concentrations of the respective m sputter cycles, i. e. ... [Pg.20]

New developments which have still to be checked for their usability in data evaluation of depth profiles are artificial neural networks [2.16, 2.21-2.25], fuzzy clustering [2.26, 2.27] and genetic algorithms [2.28]. [Pg.21]

Data evaluation. It is, of course, necessary to correlate peak area with the amount or concentration of a particular solute in the sample. Quantitation by... [Pg.246]

Ross A, Schlotterbeck G, Klaus W et al (2000) Automation of NMR measurements and data evaluation for systematically screening interactions of small molecules with target proteins. JBiomol NMR 16 139-146... [Pg.1109]

Cyclodextrin-modified solvent extraction has been used to extract several PAHs from ether to an aqueous phase. Data evaluation shows that the degree of extraction is related to the size of the potential guest molecule and that the method successfully separates simple binary mixtures in which one component does not complex strongly with CDx. The most useful application of cyclodextrin-modified solvent extraction is for the simplification of complex mixtures. The combined use of CDx modifier and data-analysis techniques may simplify the qualitative analysis of PAH mixtures. [Pg.178]

Statistical and algebraic methods, too, can be classed as either rugged or not they are rugged when algorithms are chosen that on repetition of the experiment do not get derailed by the random analytical error inherent in every measurement,i° 433 is, when similar coefficients are found for the mathematical model, and equivalent conclusions are drawn. Obviously, the choice of the fitted model plays a pivotal role. If a model is to be fitted by means of an iterative algorithm, the initial guess for the coefficients should not be too critical. In a simple calculation a combination of numbers and truncation errors might lead to a division by zero and crash the computer. If the data evaluation scheme is such that errors of this type could occur, the validation plan must make provisions to test this aspect. [Pg.146]

If, as is usual, standard deviations are inserted for e cr has a similar interpretation. Examples are provided in Refs. 23, 75, 89, 93, 142, 169-171 and in Section 4.17. In complex data evaluation schemes, even if all inputs have Gaussian distribution functions, the output can be skewed,however. [Pg.171]

Data Evaluation The Bartlett test (Section 1.7.3 cf. program MULTI using data file MOISTURE.dat) was first applied to determine whether the within-group variances were homogeneous, with the following intermediate results A = 0.1719, B = -424.16, C = 1.4286, D = 70, E = 3.50, F = 1.052, G = 3.32. [Pg.190]

The legalistic notion that only validated processes are to be used assumes that the chain of events from raw materials to analysis of the final material can be validated in globo, something that is patently impossible with the given number of adjustable parameters, not to mention unforeseen glitches. Doing the validations in bits and pieces (modules process, sampling, analysis, data evaluation, etc.) certainly helps, but does not cover the... [Pg.302]

This book focuses on statistical data evaluation, but does so in a fashion that integrates the question—plan—experiment—result—interpretation—answer cycle by offering a multitude of real-life examples and numerical simulations to show what information can, or cannot, be extracted from a given data set. This perspective covers both the daily experience of the lab supervisor and the worries of the project manager. Only the bare minimum of theory is presented, but is extensively referenced to educational articles in easily accessible journals. [Pg.438]

EPA. 1989a. Data evaluation report 30-Day feeding study in rats. Office of Pesticides and Toxic Substances. Washington, DC U.S. Environmental Protection Agency. Document no. 007163. [Pg.288]

Lucidol Product Technical Data, Evaluation of Organic Peroxides from Half-life Data Pennwalt Corp., Buffalo, NY, 1985. [Pg.320]

Lewis DFV, loannides C, Parke DV. Validation of a novel molecular-orbital approach (COMPACT) for the prospective safety evaluation of chemicals, by comparison with rodent carcinogenicity and Salmonella mutagenicity data evaluated by the United States NCI NTP. Mut Res 1993 291 61-77. [Pg.493]

NASA Panel for Data Evaluation, "Chemical Kinetic and Hydrochemical Data for Use in Stratospheric Modeling," Evaluation Number 2, JPL Publication 79-27, April 1979. [Pg.132]

An alternative for evaluating accuracy is spiking known amounts of standards to a food, as reported in several papers,although percent recoveries of spikes do not truly address the influence of the food matrix complexity on the extraction efficiency. Data evaluation procedures were developed as a manual system to assess the quality of analytical data for carotenoids in foods. ... [Pg.449]

A homogeneity index or significance coefficienf has been proposed to describe area or spatial homogeneity characteristics of solids based on data evaluation using chemometrical tools, such as analysis of variance, regression models, statistics of stochastic processes (time series analysis) and multivariate data analysis (Singer and... [Pg.129]

Table 1 Representative data evaluating data obtained from various studies for calculating the LOD and LOQ values for the extraction/analysis procedure using the 3(RMSE)/slope method to estimate the LOD/LOQ and the 799, j,seloq method to calculate the MDL and MQL... Table 1 Representative data evaluating data obtained from various studies for calculating the LOD and LOQ values for the extraction/analysis procedure using the 3(RMSE)/slope method to estimate the LOD/LOQ and the 799, j,seloq method to calculate the MDL and MQL...
PDF documents can increase the efficiency of a reviewer. Time savings can be obtained for reviewers in preparing data evaluation records owing to the ability to copy and paste (drop and drag) information from the PDF study directly into the review s application. [Pg.1068]


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Acquisition and Evaluation of Reaction Rate Data

Activation evaluation from experimental data

Ambiguity of data evaluation elementary times

Amino acid analysis data evaluation

Analytical data, evaluation

Application of Chemical Principles to Evaluate Field Data

Automatic data evaluation

Bayesian Evaluation of Reliability Data

Biological data, evaluation

Case Studies for the Evaluation of Kinetic Data

Collection and evaluation of data

Collections of critically evaluated data

Computer-Aided Data Review and Evaluation

Critical evaluation of data

Crystallizers evaluation data

Data Evaluation Techniques

Data Evaluation, Transformation and Reporting

Data Gathering and QoS Evaluation

Data Sources for Evaluation

Data bases evaluations

Data collection evaluation

Data evaluation densitometry

Data evaluation drug product stability

Data evaluation drug product stability testing

Data evaluation methods

Data evaluation multivariate analysis

Data evaluation peak height

Data evaluation products

Data evaluation programs

Data evaluation substances/products

Data evaluation testing

Data evaluation univariate analysis

Data: evaluation reduction

Decay Data Evaluation Project

EXAFS data evaluation

Electrolytes Evaluated from Calorimetric Data

Evaluated Nuclear Data Files (ENDF

Evaluated data

Evaluating Analytical Data

Evaluating Data Representativeness

Evaluating data from bioreactors

Evaluating mineralization data from

Evaluating the data

Evaluation Dynamic Data

Evaluation and Interpretation of Atmospheric Pollution Data

Evaluation and Interpretation of the Experimental Data

Evaluation for stability data

Evaluation from force-distance data

Evaluation of Existing Data

Evaluation of Experimental Data

Evaluation of Kinetic Data (Reaction Orders, Rate Constants)

Evaluation of Literature Data

Evaluation of Scattering Data

Evaluation of Thermodynamic Data

Evaluation of analytical data

Evaluation of biological data

Evaluation of data

Evaluation of kinetic data

Example of Data Collection, Evaluation, and Processing

Experimental data evaluation

Experimental data evaluation methodology

Filtration data evaluation

General Evaluation by Integration of Scattering Data

General principles for evaluating the data

Geochemical data evaluation

IUPAC Kinetic Data Evaluation

Impact evaluation data collection

Integral and Differential Reactor Data Evaluation Methods

Kinetic Data Analysis and Evaluation of Model Parameters for Uniform (Ideal) Surfaces

Material selection data, evaluating

Measurement and Evaluation of Kinetic Data

Method transfer data evaluation

Multivariate Mathematical-Statistical Methods for Data Evaluation

Multivariate Statistical Evaluation and Interpretation of Soil Pollution Data

Other Data Relevant to an Evaluation of Carcinogenicity and its Mechanisms

Phosphoric evaluated literature data

Pre-evaluation of Scattering Data

Presenting and Evaluating Performance Data A Few Caveats

Proficiency testing data evaluation

Project team evaluation data analysis

Property data evaluation

Proton evaluated literature data

Self-evaluation using data effectively

Sequencing, proteins data evaluation

Spectral data evaluation

Spectrophotometric data evaluation

Stability data evaluation

Statistical Data Treatment and Evaluation

Statistical evaluation of data

Statistical methods data evaluation

Surveys data quality evaluation

The Seven Steps of Data Evaluation

Thermochemical data, estimation evaluation

Vapor evaluated literature data

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