# stdc¶

## Purpose¶

Computes the sample standard deviation of the elements in each column of a matrix.

## Format¶

y = stdc(x)
Parameters: x (NxK matrix) – data y (Kx1 vector) – the standard deviation of each column of x.

## Examples¶

// Set the rng seed so that the random numbers produced will
// be repeatable
rndseed 94243524;

// Create a vector of random normal numbers
y = rndn(8100, 1);

// Compute the standard deviation of the column vector 'y'
std = stdc(y);


The standard deviation, in variable std, is equal to:

1.00183907


## Remarks¶

This function essentially computes sample standard deviation, s:

$s = \frac{1}{n−1}⁢×\sum_{i=1}^n(X_i−\bar{X})^2$

Thus, the divisor is $$N-1$$ rather than $$N$$, where $$N$$ is the number of elements being summed.

To convert to the population’s standard deviation, multiply by $$\sqrt{\frac{n - 1}{n}}$$:

$\sigma = s*\frac{n−1}{n}$

Functions meanc()