# Boost :

Subject: Re: [boost] [histogram] Variance
From: Bjorn Reese (breese_at_[hidden])
Date: 2018-09-20 15:32:44

On 09/17/18 22:33, Steven Watanabe via Boost wrote:

> You're thinking of the formula
> variance = \sum (x_i - mean)^2 / count = \sum x_i^2/count - mean^2

Indeed.

> That formula doesn't apply in this case, since the variance
> is the variance of the bin count, not the variance of the
> weights. The estimate for the variance is described here:

Ok, so weights are used to increase the bin count by a certain amount,
and the variance is an estimate of the spread of these weighted counts.

I had initially assumed that the per-bin variance measured how much
values that are put into a bin deviates from its center; e.g. the
midpoint of the bin, or the bin average.