The previous lesson concluded with joint and marginal distributions for the discrete case. We now consider the same concepts, but for continuous random vectors. While discrete random vectors and the associated multivariate probability functions were obtained via summing across the appropriate variable(s) within the limits of the support, analogous models are found in the continuous case via integration.