The article discusses the multivariate normal distribution, which deals with multiple random variables that are not independent. It explains how to define a multivariate normal distribution and shows that every part of it is also multivariate normal. The chapter also covers positive definite and positive semidefinite quadratic forms, as well as Cochran's theorem. It concludes by proving the independence of sample mean and sample variance for a normal population.