ds_list_variance
In probability theory and statistics, variance measures how far a set of numbers is spread out. A variance of zero indicates that all the values are identical. Variance is always non-negative: a small variance indicates that the data points tend to be very close to the mean (expected value) and hence to each other, while a high variance indicates that the data points are very spread out around the mean and from each other.
Population Variance
In general, the population variance of a finite population of size \(N\) with values \(x_i\) is given by
\( \sigma^2 = \frac 1N \sum_{i=1}^N \left(x_i - \mu \right)^2 \)
where
\( \mu = \frac 1N \sum_{i=1}^N x_i \)
is the population mean.
- ds_list_variance(id[,sample])
- Returns the variance of the values in a given list.
COPY/// ds_list_variance(id[,sample])
//
// Returns the variance of the values in a given list.
//
// id list data structure, real
// sample true if the list is made up of a sample, bool
//
/// gmlscripts.pro/license
{
var n, avg, sum, i;
n = ds_list_size(argument0);
avg = 0;
sum = 0;
for (i=0; i<n; i+=1) avg += ds_list_find_value(argument0, i);
avg /= n;
for (i=0; i<n; i+=1) sum += sqr(ds_list_find_value(argument0, i) - avg);
return sum/(n - argument1);
}
Contributors: Quimp
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