measurement result

The outcome of an analytical measurement (application of the chemical measurement process), or value attributed to a measurand. This may be the result of direct observation, but more commonly it is given as a statistical estimate derived from a set of observations. The distribution of such estimates (estimator distribution) characterizes the chemical measurement process, in contrast to a particular estimate, which constitutes an experimental result. Additional characteristics become evident if we represent $x ̂$ as follows:

$e ⎴ x ̂ = τ + e = τ + Δ + δ = μ + δ ⎵ μ$

The true value, $τ$ , is the value $x$ that would result if the chemical measurement process were error-free. The error, $e$ , is the difference between an observed (estimated) value and the true value; i.e. $e = x ̂ − τ$ (signed quantity). The total error generally has two components, bias ( $Δ$ ) and random error( $δ$ ), as indicated above. The limiting mean, $µ$ , is the asymptotic value or population mean of the distribution that characterizes the measured quantity; the value that is approached as the number of observations approaches infinity. Modern statistical terminology labels this quantity the expectation value or expected value, $E ( x ̂ )$ . The bias, $Δ$ , is the difference between the limiting mean and the true value; i.e. $Δ = μ − τ$ (signed quantity). The random error, $δ$ , is the difference between an observed value and the limiting mean; i.e. $δ = x ̂ − μ$ (signed quantity).

Source:

PAC, 1995, 67, 1699 (Nomenclature in evaluation of analytical methods including detection and quantification capabilities (IUPAC Recommendations 1995)) on page 1705

measurement result

Also contains definitions of: bias, expectation value, expected value, limiting mean