window as $(70.28\,\mu{\rm K})^2$, noise estimate as $(56.76\,\mu{\rm K})^2$, and on-sphere signal estimate as $(41.44\,\mu{\rm K})^2\pm(14.68\,\mu{\rm K})^2$. Total number of analyzed harmonics is $M=446$.

Table \[tbl\_n\] shows the results. In addition we include into the Table \[tbl\_n\] the data obtained with anomalous harmonics, and with excluded quadrupole.

We tested an effect of the harmonics excluding procedure on the signal estimation. In the case of the noise outliers caused by systematic errors and if all harmonics are orthogonal the excluding does not effect the estimation bias, but may only increase the errors in comparison to non-censored data. Simulation shows the $Q_2$ and $n$ variations are 0.9 and 0.11 respectively.

On the other hand, if the outliers are pure stochastic (i.e. we are dealing with a low-probability noise sample) the noise estimation bias may arise and, as a result may arise the signal estimation bias. We simulated this occasion for the signal and noise with the given spectrum and to examine noise outliers stronger than 2.3$\sigma$. After that we calculated the signal estimates both for censored and non-censored spectra.

After 1228 simulations we have found 500 events with the outliers. The corresponding estimates are: $\langle
n_{censor}-n_{full}\rangle=0.07\pm 0.08$ $\langle
Q_{censor}-Q_{full} \rangle=-0.4\pm 0.83$. It 