Gaussian Random Vectors

This lecture covers Gaussian vectors, multivariate normal distribution, moment generating functions, independence of random vectors, density functions, affine transformations, isosurfaces, and coordinate distributions. It also discusses diagonal covariance matrices, chi-square and F distributions, Gaussian quadratic forms, and the Central Limit Theorem for weighted sums of random variables.