var
var(v[, region])
Compute the sample variance of a vector or array v
, optionally along dimensions in region
. The algorithm will return an estimator of the generative distribution's variance under the assumption that each entry of v
is an IID drawn from that generative distribution. This computation is equivalent to calculating sumabs2(v  mean(v)) / (length(v)  1)
. Note: Julia does not ignore NaN
values in the computation. For applications requiring the handling of missing data, the DataArray
package is recommended.
Examples

Compute sample variance of a vector:
julia> v = [1, 2, 3, 4, 5]; julia> var(v) 2.5
This example calculates the sample variance of the vector
v
. 
Compute sample variance along a specific dimension of an array:
julia> A = [1 2 3; 4 5 6; 7 8 9]; julia> var(A, 1) 6element Array{Float64,1}: 9.0 9.0 9.0
Here, the
var
function calculates the sample variance along the first dimension (1
) of the arrayA
.  Compute sample variance along multiple dimensions of an array:
julia> B = [1 2 3; 4 5 6; 7 8 9]; julia> var(B, (1, 2)) 1element Array{Float64,1}: 6.666666666666667
In this example, the
var
function calculates the sample variance along both dimensions (1
and2
) of the arrayB
.
Note: Julia does not ignore NaN
values in the computation. If your data contains NaN
values and you want to handle missing data, it is recommended to use the DataArray
package.
Please let me know if there's anything else I can help you with!
See Also
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