Paper
3 April 1995 Role of X-axis uncertainties on standard curves
Michael L. Johnson
Author Affiliations +
Abstract
The commonest method for the determination of standard curves is to use a least-squares technique to fit a function to a set of standard data. This fitted curve is then used to interpolate values from the standard curve. The problem addressed is that the standard data used for this process will usually contain experimental uncertainties in the X-axis (the independent variable) and in the Y-axis (dependent variable). When such X-axis uncertainties exist in the data it is statistically invalid to apply a least-squares procedure to evaluate the coefficients of the standard curve. This statistical invalidity generally cannot be corrected by the application of an `appropriate weighting factor.' However, a simple maximum likelihood procedure can be used to correctly consider the uncertainties in both the X-axis and Y-axis.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Michael L. Johnson "Role of X-axis uncertainties on standard curves", Proc. SPIE 2386, Ultrasensitive Instrumentation for DNA Sequencing and Biochemical Diagnostics, (3 April 1995); https://doi.org/10.1117/12.206021
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KEYWORDS
Proteins

Information operations

Solids

Calibration

Data centers

Chromatography

Health sciences

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