The problem of falsified counting statistics (deviating from Poisson
distribution) sometimes arises even from (wrong) conversion of 0D
detector data (typically when originally cps have been stored and the
counting time got lost in the conversion), and is quite common when 1D
detector data are
If this rule is broken, such as the mode in
FIT2D that smooths patterns by pixel-splitting) then one introduces
correlation between points in the pattern
Hi Brian, your comment has triggered me it seems :-)
For SAXS and PDF it could be better to under-sample the data (see end),
but for
Tony. If you want the statistics to be the same as for larger steps you
should be adding the counts from your PSD channels, not averaging them.
That said, with an x-ray PSD you perhaps have so much intensity that
uncertainties in your refined parameters due to counting statistics may be
small
Hi Tony
If you want to have a look at what the uncertainties are doing, then try
scanning over a peak a couple of dozen times (maybe with a few different mA
settings on the tube, maybe with some different step times) to collect a
range of different intensities. The standard deviation of the "raw"
