Covariance

Overview


Covariance is similar to the variance. It is defined
{% cov(X,Y) = \mathbb{E}[(X- \mathbb{E}[X])(Y - \mathbb{E}[Y])] %}
It is a measure of how two random variables are related. If they are independent, covariance will be zero.

Topics


  • Correlation - a normalized version of the covariance
  • Vector Covariance - states the covariance in matrix format
  • Diagonalization

Implementation





let mt = await import('/lib/statistics/moments/v1.0.0/moments.mjs');
let numbers = [
	[1,2],
	[2,2],
	[3,6],
	[1,3],
	[4,4],
];
let covariance = mt.covariance(numbers);
Try it! 



let mt = await import('/lib/statistics/moments/v1.0.0/moments.mjs');
let numbers = [
    {first:1,second:2},
    {first:2,second:2},
    {first:3,second:6},
    {first:1,second:3},
    {first:4,second:4},
];
let covariance = mt.covariance(numbers);
Try it!