Spurious accuracy

Absolute accuracy and precision are impossible to achieve, owing to the limitations of measuring systems. It is particularly important to avoid spurious accuracy in the presentation of results include only those digits which the accuracy of the measuring system implies. This type of error is common when changing units (e.g. inches to metres) and in derived data, especially when calculators give results to a large number of decimal places. 

Since the modest aim of our analysis was to illuminate the long-run trend in the perception of American chemical research in Germany, rather than to offer a detailed analysis of Chemische Berichte, an elaborately constructed sample of citations would have yielded spurious accuracy. The citations to be examined were selected in the following manner ... 

After a simple Fourier inversion of a set of magnetic structure factors MbU, one can retrieve the magnetisation density. A much better result, e.g. the most probable density map, can be obtained using the Maximum Entropy (MaxEnt) method. It takes into account the lack and the uncertainty of the information not all the Bragg reflections are accessible on the instrument, and all the values contained in the error bars are satisfactory and have to be considered. However, as this method extracts all the information contained in the data, it is important to keep in mind that it may show spurious small details associated to a low accuracy and/or a specific lack of information located in (/-space. 

The accuracy with which a system can measure lifetimes depends on a number of different factors including calibration of the instrument, the number of detected photons and also the efficiency of the analysis routines. In addition, sources of background and scattered light should be eliminated. Emission filters should be chosen with great care to make sure that no scattered laser light reaches the detector. Detection of scattered excitation light results in a spurious fast component in the decay and complicates the interpretation of the data. The choice of emission filters is much more critical in FLIM than in conventional fluorescence intensity imaging methods. 

A redox couple is formed as soon as the silver within the paint starts to corrode. Clearly, this can be disastrous. In addition, the silver can enter into solution if the contact is immersed in a reactive solution, again greatly complicating analytical measurements. Thirdly, the silver can be oxidized (e.g. to Ag2 0 or Ag ), thus causing spurious voltammetry peaks and removing all accuracy or chance of computing the faradaic efficiency. 

The amount of heat generated by a reaction is the same whether the reaction takes place in one step or in several steps. Hence, A//values (and, thus, AG values) are additive. This law, also known as the Law of Constant Heat Summation, was the earliest example of the Additivity Principle, which also states that AG values are additive. In biochemical processes, especially when dealing with multiple steps as in protein folding, application of the Additivity Principle can give spurious results if the accuracy and precision of the thermodynamic parameters is insufficient. 

One limitation on the use of isotope peak intensities to determine the molecular formula is that the molecular ion must be relatively intense, otherwise the isotope peaks will be too weak to be measured with the necessary accuracy. Difficulty may also arise from spurious contributions to the isotope peak intensities from the protonated molecular ion, from weak background peaks or from impurities in the sample. In any event the method is only reliable for molecules having molecular weights up to about 250-300. 

An important lesson learned from the study is that there is a trade-off between maximizing prior information utilization and robustness concerning the accuracy of such information. Multivariate calibration methods range from explicit methods with maximum use of prior information (e.g., OLS, least robust when accurate model is not obtainable), hybrid methods with an inflexible constraint (e.g., HLA), hybrid methods with a flexible constraint (e.g., CR), and implicit methods with no prior information (e.g., PLS, most robust, but is prone to be misled by spurious correlations). We believe CR achieves the optimal balance between these ideals in practical situations. 

Due to the hyperbolicity and nonlinearity of the model equations, associated with possible shocks in granular flows over non-trivial topography, numerical solutions with the traditional high-order accuracy methods are often accompanied with numerical oscillations of the depth profile and velocity field. This usually leads to numerical instabilities unless these are properly counteracted by a sufficient amount of artificial numerical diffusion. Here, a non-oscillatory central (NOC) difference scheme with a total variation diminishing (TVD) limiter for the cell reconstruction is employed, see e.g. [4], [12] we obtain numerical solutions without spurious oscillations. In order to test the model equations, we consider an ideal mountain subregion in which the talweg is defined by the slope function... 

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