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Poisson errors and adaptive rebinning in X-ray Powder Diffraction Data



Marcus H. Mendenhall


Abstract This work provides a short summary of techniques for formally-correct handling of statistical uncertainties in Poisson- statistics dominated data. Correct assignment of uncertainties for low counts is documented. We describe a technique for adaptively rebinning such data sets to provide more uniform statistics across a pattern with a wide range of count rates, from a few (or no) counts in a background bin to on-peak regions with many counts. This permits better plotting of data and analysis of a smaller number of points in a fitting package, without significant degradation of the information content of the data set. Examples of the effect of this on a data set are given.
Powder Diffraction


statistics, x-ray diffraction, xrd, poisson, data analysis, adaptive


Mendenhall, M. (2018), Poisson errors and adaptive rebinning in X-ray Powder Diffraction Data, Powder Diffraction, [online], (Accessed April 14, 2024)
Created October 10, 2018, Updated December 20, 2018