carefull now, i'm a bit thick.
i'm using a machine/software at work to collect data, and analyse it.
there are filters i can apply to reduce the noise/spikes in the data.
(if one data point says 0.05, but the other 500 say 0.01ish, then i don't care about the 0.05)
the filter has a setting - a standard deviation value.
(default setting = 3)
now, my less-than-confident understand of 'standard deviation' is that the value is in the same units as the data (in this case, millimeters).
and standard-deviation is the square-root of the average-squared-deviation.
and it's given the name 'sigma'
so, a default setting of 3 will be letting all my data through - right?
and if i want to remove the spikes, i should set the filter to 0.02ish?
But, i've got conflicted understanding; the bell-curve distribution diagram that keeps popping up on google says that +/- 1 sigma covers 68% of the data, and 2 will cover 95%.
so, what's the difference between my standard deviation (sigma) value of 0.01ish and the standard deviation curve sigma?
and what do i set my filter to?
if i get these numbers wrong, we won't be able to calculate our path through hyper-space, and we'll overshoot the earth by 12 light years...