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# Changes

m
~~<br>~~where <math>\langle I_{hkl}\rangle</math> is the average of symmetry- (or Friedel-) related observations of a unique reflection. It can be shown that this formula results in higher R-factors when the redundancy is higher. In other words, low-redundancy datasets appear better than high-redundancy ones, which obviously violates the intention of having an indicator of data quality!

→Data quality indicators

</math>

<br>

* Redundancy-independant version of the above:

<math>

</math>

<br>

which unfortunately results in higher (but more realistic) numerical values than R<~~br~~sub>sym</sub> / R<sub>merge</sub>

* measuring quality of averaged intensities/amplitudes:

for intensities use

<math>

R_{p.i.m.} (or R_{mrgd-I}) = \frac{\sum_{hkl} \sqrt \frac{1}{n} \sum_{j=1}^{n} \vert I_{hkl,j}-\langle I_{hkl}\rangle\vert}{\sum_{hkl} \sum_{j}I_{hkl,j}}

</math>

<br>

</math>

<br>

with <~~br~~math>\langle F_{hkl}\rangle</math> defined analogously as <math>\langle I_{hkl}\rangle</math>.

=== Model quality indicators ===