## Calculating covariance of two sets of data points

Unbiased covariances are given by the formula `cov(X, Y) = sum [(xi - E(X))(yi - E(Y))] / (n - 1),`

where `E(X)`

is the mean of `X`

and `E(Y)`

is the mean of the `Y`

values. Non-bias-corrected estimates use `n`

in place of `n - 1`

. To determine if the covariance is bias corrected or not, we need to set an additional, optional parameter called `biasCorrected `

which is set to true by default.

### How to do it...

Create a method that takes two one-dimensional double arrays. Each array represents a set of data points:

public void calculateCov(double[] x, double[] y){

Calculate the covariance of the two sets of data points as follows:

double covariance = new Covariance().covariance(x, y, false);

### Note

For this recipe, we have used non-bias-corrected covariance, and therefore, we have used three parameters in the

`covariace()`

method. To use unbiased covariance between two`double`

arrays, remove the third parameter,`double covariance = new Covariance...`