In earlier lessons, we discussed the absence or presence of a relationship between variables, and how to model that relationship. We discussed joint probability functions, conditional probability functions, and hierarchical structures using multiple variables. However, we have not discussed how to assess the strength of that relationship. The covariance and correlation are measures of the strength of the linear association between two variables. We discuss and illustrate the concepts of covariance and correlation, their interpretation, and illustrate them through the bivariate normal distribution.