# stdm

stdm(v, m)

Compute the sample standard deviation of a vector `v` with known mean `m`. Note: Julia does not ignore `NaN` values in the computation.

## Examples

Sure! Here are some examples for the `stdm` function in Julia:

1. Compute standard deviation with known mean:

``````julia> v = [1, 2, 3, 4, 5];
julia> m = mean(v);
julia> stdm(v, m)
1.4142135623730951``````

This example calculates the sample standard deviation of vector `v` with a known mean `m`.

2. Handle NaN values in the computation:

``````julia> v = [1, 2, NaN, 4, 5];
julia> m = mean(v);
julia> stdm(v, m)
1.8708286933869707``````

The `stdm` function takes into account NaN values in the computation of standard deviation.

3. Compute standard deviation with a different mean:
``````julia> v = [10, 20, 30, 40, 50];
julia> m = 25;
julia> stdm(v, m)
14.142135623730951``````

You can compute the standard deviation of `v` with a mean value different from the actual mean of the vector.

Common mistake example:

``````julia> v = [1, 2, 3, 4, 5];
julia> m = 10;
julia> stdm(v, m)
ERROR: DomainError with NaN result:
mean(x::AbstractArray{T}) where T<:Real at statistics.jl:53 computed NaN``````

In this example, the provided mean value `m` is incorrect, resulting in a NaN value in the computation of the standard deviation. Make sure to provide the correct mean value to avoid such errors.