Errors in quantitative electron microprobe analysis arise from many sources including those associated with sampling, specimen preparation, instrument operation, data collection, and analysis. The relative magnitudes of some of these factors are assessed for a sample of NiAl used to demonstrate important concerns in the analysis of even a relatively simple system measured under standard operating conditions. The results presented are intended to serve more as a guideline for developing an analytical strategy than as a detailed error propagation model that includes all possible sources of variability and inaccuracy. The use of a variety of tools to assess errors is demonstrated. It is also shown that, as sample characteristics depart from those under which many of the quantitative methods were developed, errors can increase significantly.

X-ray counting statistics plays a key role in establishing confidence limits in composition determination by X-ray microanalysis. The process starts with measurements of intensity on one or more samples and standards as well as related background determinations. Since each individual measurement is subject to variability associated with counting statistics, it is necessary to combine all of the counting variability according to established mathematical procedures. The next step is to apply propagation of error calculations to equations for quantitative analysis and determine confidence limits in reported composition. Similar concepts can also be applied to trace element determination. This approach can then be combined with spectral simulation modeling, making it possible to predict detectability limits without additional measurements.