# Changeset 2751 for trunk/doc

Ignore:
Timestamp:
Jun 24, 2012, 11:11:17 AM (9 years ago)
Message:

minor correction

File:
1 edited

### Legend:

Unmodified
 r2695 This estimator fulfills that it is invariant under a rescaling and having a weight equal to zero is equivalent to removing the data point. Having all weights equal to unity we get \f$\sigma=\frac{\sum point. Having all weights equal to unity we get \f$ s^2=\frac{\sum (x_i-m)^2}{N} \f\$, which is the same as returned from Averager. Hence, this estimator is slightly biased, but still very efficient.