Analytical variance

The coefficient of variation must be 6% or less. This figure includes both the sampling and the analytical variance. 

In order to determine the sampling variance accurately, it is necessary to minimize the individual components of analytical variance as much as possible. Once the sampling constant(s) are determined, one can predict what the magnitude of the sampling variance should be for a given analyte and for various masses of the sample of a given material. 

The observed elemental variances of each measurement experiment and the components of the analytical variances discussed above are used to calculate variances due to heterogeneity for each element which are converted to relative uncertainties Rj. These relative uncertainties then provide the input in the two relevant Equations (4.3 and 4.4) that are commonly used to express elemental homogeneity of a sample as a function of sample mass (w). 

Estimate the analytical variance S d) by one-way analysis of variance (2 x 12p) using each well value (estimation variance between each well and each portion). 

Estimation of the analytical variance by one-way ANOVA (2 portions x 10 laboratories). 

The analytical variance can be determined by carrying out replicate analysis of samples that are known to be homogeneous. You can then determine the total variance. To do this, take a minimum of seven laboratory samples and analyse each of them (note that Sample characterizes the uncertainty associated with producing the laboratory sample, whereas sanalysis w h take into account any sample treatment required in the laboratory to obtain the test sample). Calculate the variance of the results obtained. This represents stQtal as it includes the variation in results due to the analytical process, plus any additional variation due to the sampling procedures used to produce the laboratory samples and the distribution of the analyte in the bulk material. 

Analytical variance is defined as the coefficient of variance or relative standard deviation that is directly related to the experimental approach. This variance does differ in accordance with the technology platform being used and is... 

Thermal desorption mass spectrometry is a rapid technique for the determination of oil in soils and sediments [9]. This method exhibited lower analytical variance compared to Soxhlet extraction, i.e. followed by conventional analysis. The analysis time for wet soil samples was about 20min. 

Many classes of organic compounds adsorbed by this resin can be desorbed by solvents such as ether (or acidic methanol and ether). The acidic solvents can be concentrated to remove inorganic acid, but some residual inorganic acid always remained in the concentrated eluants. Residual acid, or possible trace of water in the concentrated eluants, caused analytical variances when methylation was attempted. Therefore, quinaldic acid, trimesic acid, and 5-chlorouracil were analyzed by HPLC rather than by GC-FID. 

Lame and Defize [334] showed that the fundamental sampling error for soil only affects the analytical variance when sample sizes are less than 10 g [335]. For larger samples, the variance is determined by the segregation error. A sampling board method for estimation of the segregation error was described. Skalski and Ward [335] showed that a two-way compositing strategy could be used to attribute detected contamination in composited samples directly to constituent samples without further analyses. 

Nutrient Analytical variance Target value Acceptable range... 

If the above approach creates practical problems, an alternative is to perform single analyses on a minimum of five test portions of the study sample. The standard deviation of replicate analysis results is an indicator of sample homogeneity and method precision. The disadvantage of this approach is that it does not provide a simultaneous measure of the analytical variance under the homogeneity test conditions. Analytical variance must be estimated from historical data (e.g. method validation) or spiked recoveries run with the homogeneity test samples. 

For many mathematical operations, including addition, subtraction, multiplication, division, logarithms, exponentials and power relations, there are exact analytical expressions for explicitly propagating input variance and covariance to model predictions of output variance (Bevington, 1969). In analytical variance propagation methods, the mean, variance and covariance matrix of the input distributions are used to determine the mean and variance of the outcome. The following is an example of the exact analytical variance propagation approach. If w is the product of x times y times z, then the equation for the mean or expected value of w, E(w), is ... 

The G-BASE project has used several statistical packages to perform this nested ANOVA analysis (e.g., Minitab and SAS). It currently uses an MS Excel procedure with a macro based on the equations described by Sinclair (1983) in which the ANOVA is performed on results converted to logio (Johnson, 2002). Ramsey et al. (1992) suggest that the combined analytical and sampling variance should not exceed 20% of the total variance with the analytical variance ideally being <4%. 

Different T3 immunoassays may show unexplained discrepancies between values for the same sera. Results from inter-laboratory quality assurance schemes also demonstrate a higher analytical variance for T3 than for T4 methods. Many factors have been suggested as accounting for these disparities, such as the lower quantity of T3 in sera, differences in antisera cross-reactivity, protein interferences, and different assay limits of detection. ... 

Clark, M.J.R, Laidlaw, M.C.A, Ryneveld, S.C. and Ward, M.I. (1996) Estimating sampling variance and local environmental heterogeneity for both known and estimated analytical variance. Chemosphere, 32, 1133-1151. 

During this optimisation programme, samples of eel, fish oil, mussel and sewage sludge were prepared for intercomparison. Data from analysis of a crude eel extract and a refined (cleaned-up) sample were compared to test the variance associated with different methods of sample preparation. The clean-up methods included gel permeation chromatography, saponification, concentrated sulphuric acid treatment, alumina and silica-gel column chromatography. The differences in results of the within and between clean-up methods did not significantly influence the overall analytical variance after the appropriate optimisation. 

Shurubor, Y.I. et al., Biological variability dominates and influences analytical variance in HPLC-ECD studies of the human plasma metabolome, BMC Clin. Pathol., 1, 9, 2007. 

Little is gained by improving the analytical variance to less than one-third the sampling variance. It is better to analyze more samples using a faster, less precise method. 

Positive match The chromatographic patterns of the samples submitted for comparison are virtually identical and the observed differences between the spill sample and suspected source are caused and can be explained by the acceptable analytical variance and weathering effects. 

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