The article discusses how experiments can involve multiple numerical quantities, leading to the need for studying multidimensional random variables. It explains how joint distributions of multiple random variables can determine individual distributions, but not always vice versa. The concept of independence among random variables is explored, along with functions of multiple variables and their distributions. The article also covers moments, covariance, correlation, conditional expectation, and ordered observations.