Dear Ifeffit members, I have some fundamental questions regarding noisy data, and I am wondering how to tell whether the data quality worth doing Fourier transformation/EXAFS fitting or not. For example, the attached MnO chi(k) data becomes noisy from 7 Å-1 when it was measured up to 12 Å-1. The deglitching (left: red -> blue) mitigated the strong dips but the high-k end still has too much noise. I practiced the FT and fitting the 1st and 2nd shells by using the lower part. But My questions here are: 1) How noisy would be too noisy? Like the data between 8 and 10 Å-1 in the attached file, can they still be included for the FT? 2) We can choose the high-k end based on the signal-to-noise ratio, but to what extend? With data being noisy from even 5 or 6 Å-1, can they still be used? 3) For fitting the 1st and 2nd shells, I still lack of clear understanding how the high-k portion can influence. If I measure a set of samples, and one of them has much noisy data so a shorter k-range is picked up for background subtraction and FT. In this case, can I still consider the change or evolution in the fitted parameters systematic? Thank you in advance, Best regards, Yang
