The probability theory seen in Year Four described single events; now we take a step forward and study random variables, that is, quantities whose value depends on chance, together with their probability distributions. The chapter introduces the mean, variance and standard deviation of a distribution, then reviews the most important discrete models — the binomial, the Poisson and the hypergeometric — and the continuous models — the Gaussian (the Gaussian bell curve) and the exponential — closing with the cumulative distribution function that unifies them. Two cultural appendices show how far these ideas reach: the Shannon entropy, which measures the uncertainty of a random source, and modular arithmetic with RSA cryptography, where elementary arithmetic becomes the foundation of digital security.