Towards properly controlled analytical measurement methods

It is of great practical importance to develop simple methods for the automatic detection ofthe controlled state of the analytical method being applied. The key point is to find quantities that greatly affect the quality of the analytical results and that can be easily estimated during the measurement process from the measured data. The signal-to-noise ratio has proved to be such a quantity in gas chromatographic methods. The statistical properties of the estimation of the signal-to-noise ratio from gas chromatographic data have been investigated. The suggested practical method for estimating the signal-to-noise ratio proved to be biased from a mathematical statistical point of view, but the bias is usually not greater than 10%. It has been shown by practical examples that the signal-to-noise ratio affects the quality of the analytical results and it is easy to estimate its value from practical data

Investigation of the steady state measurement process

Based on the role of steady state concept in the model of analytical chemical measurement and deduction, the definition of ‘practically sleady slate’ (PSS) has been inlroduced. The defnition does not require the process to be in steady state in a strictly mathematical sense. In order to fulfil the requiremenls of ‘practically steady state’ the random error and the syslematic error must vary within a suitable limit, and the expected fgure for the measured value must be within a specified range

Towards properly controlled analytical measurement methods

It is o f great practical importance to develop simple methods for the automatic detection of the controlled state of the analytical method being applied. The key point is to find quantities that greatly affect the quality of the analytical results and that can be easily estimated during the measurement process from the measured data. The signal-to-noise ratio has proved to be such a quantity in gas chromatographic methods. The statistical properties of the estimation of the signal-to-noise ratio from gas chromatographic data have been investigated. The suggested practical method for estimating the signal-to-noise ratio proved to be biased from a mathematical statistical point of view, but the bias is usually not greater than 10%. It has been shown by practical examples that the signal-to-noise ratio affects the quality of the analytical results and it is easy to estimate its value from practical data