I heard that linear algebra especially matrix algebra including singular value decomposition, symmetric, Hermitian, conjugate transpose, unitary geometry, transposes, and spectral theory show up in multivariate statistics and stochastic processes. Is multivariate statistics really dependent on understanding advanced linear algebra? Should I avoid multivariate statistics and stochastic processes if the advanced linear algebra and diagonalization methods of matrices don't make sense to me?
Whenever I read a stochastic processes book or book on multivariate statistics, the matrix algebra used when doing change of basis scares me and confuses me.
I've also looked at a book on probability theory which is a prerequisite for stochastic processes which is applied calculus and all the computations or proofs on for example leverage and Cook's distance seem messy and not elegant. I don't think I'd like mathematical stats.