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The normal practice of using time averages for the data input partly reduces the dynamic problems. However, that does not completely resolve timing inconsistencies for infrequently-sampled data like lab analyses.
This use of average values, like a [[moving average]], acts as a [[low-pass filter]], so high frequency noise is mostly eliminated. The result is that, in practice, data reconciliation is mainly making adjustments to correct systematic errors like biases
===Necessity of removing measurement errors===
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