The average of a matrix is simple, however, how to calculate variance and standard deviation of a matrix?

Variance is defined as:

Standard deviation is defined as:

Here is an example to show how to calculate them.

## Preliminaries

import numpy as np

## Create a matrix

m = np.array([[1, 2, 3], [4, 5, 6]])

The output is:

array([[1, 2, 3], [4, 5, 6]])

## Calculate the average of this matrix

avg = np.mean(m)

The output is *3.5*

## Calculate the variance

var = np.var(m)

The output is *2.9166666666666665*

## Calculate standard deviation

std = np.std(m)

The output is *1.707825127659933*