 This more general concept of a random element is particularly useful in disciplines such as graph theory, machine learning, natural language processing, and other fields in discrete mathematics and computer science, where one is often interested in modeling the random variation of non-numerical data structures.In some cases, it is nonetheless convenient to represent each element of formula_15 using one or more real numbers.In this case, a random element may optionally be represented as a vector of real-valued random variables (all defined on the same underlying probability space formula_4, which allows the different random variables to covary).