Multivariate normality refers to a statistical assumption that a set of variables are jointly normally distributed, meaning any linear combination of these variables is also normally distributed. This assumption is crucial in multivariate statistical analyses, such as multivariate regression and factor analysis, as it underpins the validity of inferential procedures and tests within these frameworks.