Keith Jahoda's response to a user question directed to xtehelp in August 2004: When you use SAEXTRCT to collect your spectra, it estimates an error equal to the square root of the number of counts. For the data, this is unquestionably correct. For the background spectrum, however, this overestimates the errors since the PCABACKEST output is based on the average of a huge amount of data. (The details of "huge" are variable since only data with similar L7 rates contributes to the background model for each value of L7). The statistical error on the background is thus related to the amount of data that went into the background model and not the length of your observation. It is almost certainly true that the Poisson errors are dominated by the observed data, and you could set the background error column to zero. (This obviously underestimates the error on the background, but the reduced chi-square values would be only very slightly higher than 1). If you want a better estimate of the errors in each spectral channel, you could compare the estimated background in adjacent channels. As there is no reason to believe that the background spectrum isn't smooth in places where there are not obvious line features, you can probably use the channel to channel variation as a robust estimator.