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The expected squared deviation of a random variable from its mean; or, the average squared deviation of data about their mean.

1 vote

Variance of sample median

you can also calculate: \begin{align} \sigma^2_{\tilde{\mu}_s} \approx \sum_{i=0}^{N-1} {N-1 \choose i} \left(\frac{1}{2}\right)^{1-N} \left(x_i - \tilde{\mu}_s\right)^2  \end{align} Analogously to the variance
Wolfgang Brehm's user avatar
0 votes

The variance of the weighted median and optimal weights

The variance introduced to the nominator by each weight is therefore $^1/_4$ the weights squared and the variance of $c$ is approximadted by the sum of individual variances divided by the normalization … Therefore the the inverse weighted cumulative distribution of $c$ is the same variance as the weighted median. …
Wolfgang Brehm's user avatar
4 votes
2 answers
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The variance of the weighted median and optimal weights

weighted sample mean ${_w\mu}$ is the estimate for the population mean with the lowest variance $\sigma^2_{_w\mu}$. … This also makes a nice connection to inverse variance weights that are optimal for the weighted average, because in the weighted median, asymptotically each sample contributes a variance inversely proportional …
Wolfgang Brehm's user avatar