Method of processing data derived from a sample

A method of processing data derived from a sample, comprising processing an initial data set of elements derived from a detection by a detector for calibration, the data set comprising elements representing nuisance signals and detection signals, the processing of the initial data set comprising:

• fitting a distribution model to the initial data set to create a nuisance distribution model;
• setting a signal strength value, and selecting elements in the initial data set having a magnitude greater than the signal strength value as a set of defect candidates;
• fitting a distribution model to the set of defect candidates to create a defect distribution model of detection signals;
• and
• determining a signal strength threshold dependent on at least the defect distribution model, the determining comprising correcting the defect distribution model, desirably the correcting being suitable for correcting for overlap in magnitude between elements representative of nuisance signals and detection signals.