The distribution of waiting times between events that happen at a constant rate; the law of radioactive decay.The exponential distribution models the time between events in a process where events occur continuously and independently at a constant average rate. It is the continuous analogue of the geometric distribution and is memoryless: the probability of waiting another minute does not depend on how long you have already waited. This makes it the natural model for radioactive decay, where each atom has a constant probability of decaying per unit time.
The distribution was first derived by the French mathematician Siméon Denis Poisson in the early 19th century, though it was later formalized in the context of radioactive decay by Ernest Rutherford and Hans Geiger in 1910.
If events occur at a rate λ per unit time, the probability density function is f(t) = λ * e^(-λt) for t ≥ 0. The mean waiting time is 1/λ, and the variance is 1/λ². The memoryless property means that P(T > t+s | T > s) = P(T > t), which is unique to the exponential distribution among continuous distributions.
It is used in reliability engineering to model the lifetime of components, in queueing theory for service times, and in finance for modeling the time between trades.
The exponential distribution is the only continuous distribution with the memoryless property, meaning a light bulb that has lasted 1000 hours is no more likely to fail in the next hour than a brand-new one.

