A random variable is a fundamental concept in statistics that links the outcomes of random events to numerical values. Unlike traditional variables in algebra, which can only take a single value at a time, a random variable can assume multiple values, each associated with a specific probability. This allows for the representation of uncertainty in various scenarios, such as flipping coins or rolling dice ¹².

There are two main types of random variables: discrete and continuous. A discrete random variable can take on a countable number of distinct values, such as the number of heads obtained when flipping a coin multiple times. In contrast, a continuous random variable can take on an infinite range of values within a given interval, such as measuring the height of individuals ¹².

The probability distribution of a random variable describes how probabilities are assigned to its possible outcomes. For discrete random variables, this is often represented by a probability mass function, while for continuous random variables, it is represented by a probability density function ¹⁴.