Hi !
I recorded 4 sets of R1 and would like to use them all and, so, extract
a mean value and also an associated error...
I would like to get the opinion of someone maybe more used with
statistics than me...
I thought about :
1. calculating the mean error
2. calculating the standard error (should be the best way, no)
3. calculating the standard deviation
4. extracting an error by calculating the extremes the value can reach
in every dataset based on the error of each dataset
What would the best error to use in a statistical point of view, but
also in a model-free point of view..?
Also, is there a way to use both the errors in the datasets and a error
extrated for the observed deviation of data..?
Note that the errors from each datasets were calculated directly from
the fits, here using the 'autoFit.tcl' script from NMRPipe with data
processed as Gaussian lines.
Also, in the case of duplicates or triplicates, should one use the same
approcah ?
Thanks !
Séb :)
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| |
|| Sebastien Morin ||
||| Etudiant au PhD en biochimie |||
|||| Laboratoire de resonance magnetique nucleaire ||||
||||| Dr Stephane Gagne |||||
|||| CREFSIP (Universite Laval, Quebec, CANADA) ||||
||| 1-418-656-2131 #4530 |||
|| ||
|_______________________________________________|
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