Covariance and correlation

We have seen how to show the relation between two or more variables visually, using the scatter plot.

Let’s see now how to measure a relation between two variable in a mathematical way.


Covariance is a type of value used in statistics to describe the linear relationship between two variables. It describes both how far the variables are spread out (a measure of how much one variable goes up when the other goes up) and the nature of their relationship: a positive covariance indicates that when one variable increases, the second increases and when one decreases the other decreases; on the other hand if the covariance is negative it means that an increase in one will cause a decrease in the other.

This answer on CrossValidated shows a nice visual explanation of covariance based on scatter plots:

Red “rectangles” between pairs are positive relations, blue are negative.

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