Search results
Results from the WOW.Com Content Network
A calibration curve plot showing limit of detection (LOD), limit of quantification (LOQ), dynamic range, and limit of linearity (LOL).. In analytical chemistry, a calibration curve, also known as a standard curve, is a general method for determining the concentration of a substance in an unknown sample by comparing the unknown to a set of standard samples of known concentration. [1]
The silver concentration in the test sample is the x-intercept of the plot. The dilution factor is multiplied by this initial concentration to determine the original concentration. Matrix effects occur even with methods such as plasma spectrometry , which have a reputation for being relatively free from interferences.
From the definition of reactivity ratios, several special cases can be derived: >> If both reactivity ratios are very high, the two monomers only react with themselves and not with each other. This leads to a mixture of two homopolymers. >. If both ratios are larger than 1, homopolymerization of each monomer is favored.
Since this is a biased estimate of the variance of the unobserved errors, the bias is removed by dividing the sum of the squared residuals by df = n − p − 1, instead of n, where df is the number of degrees of freedom (n minus the number of parameters (excluding the intercept) p being estimated - 1). This forms an unbiased estimate of the ...
A graphical representation of the current and voltage properties of a transistor; the bias is selected so that the operating point permits maximum signal amplitude without distortion. In electronics , biasing is the setting of DC ( direct current ) operating conditions (current and voltage) of an electronic component that processes time-varying ...
The Gran plot is based on the Nernst equation which can be written as = + {+} where E is a measured electrode potential, E 0 is a standard electrode potential, s is the slope, ideally equal to RT/nF, and {H +} is the activity of the hydrogen ion.
In chemical analysis, matrix refers to the components of a sample other than the analyte [1] of interest. The matrix can have a considerable effect on the way the analysis is conducted and the quality of the results are obtained; such effects are called matrix effects. [2]
However, because income is equal to expenses plus savings by definition, it is incorrect to include all 3 variables in a regression simultaneously. Similarly, including a dummy variable for every category (e.g., summer, autumn, winter, and spring) as well as an intercept term will result in perfect collinearity. This is known as the dummy ...