The Multivariate Normal Distribution

Many of the inferential methods used in logistic regression depend on the assumption that the estimates have a sampling distribution that is, asymptotically, a multivariate normal distribution.


The multivariate normal is defined by its distribution function that looks very similar to the univariate case. However it involves a random vector and a variance-covariance matrix.


The multivariate normal distribution has some very nice properties that are often behind the scene in output produced by software (including SAS)


Two additional properties of the multivariate normal distribution.


The slides used in the videos are found here