The exponential is the model of waiting times: how long passes before the next decay, the next arrival, the next failure. It is closely tied to the Poisson distribution (which counts the events) and to radioactive decay.

Property — XExp(λ)X\sim\text{Exp}(\lambda)

Models the waiting times between events (decays, arrivals, failures). f(x)=λeλx for x0,f(x)=0 for x<0.f(x) = \lambda\,e^{-\lambda x} \text{ for } x\ge 0, \qquad f(x)=0 \text{ for } x<0. Mean 1/λ1/\lambda, variance 1/λ21/\lambda^2. The cumulative distribution function is F(x)=1eλxF(x) = 1-e^{-\lambda x}.

Remark — Connection with ODEs

The exponential distribution is the same function that appears in the solution of the ODE y=λyy'=-\lambda y: radioactive decay. This is no coincidence: the survival probability P(X>t)=eλtP(X>t) = e^{-\lambda t} satisfies exactly that differential equation.

Exponential distribution for three values of λ\lambda: large λ\lambda means short waits (a curve that decays quickly, starting high), small λ\lambda long waits.

Topics: Distribuzioni probabilita
Concepts: Densita di probabilita · Distribuzione esponenziale · Funzione di ripartizione
Skills: Interpretare grafico · Modellizzare