# Exponential Distribution Formula

The exponential distribution in probability is the probability distribution that describes the time between events in a Poisson process.

#### Probability Density Function

$\large f(x \lambda ) = \left\{\begin{matrix} \lambda e^{-\lambda x} & x >= 0,\\ 0 & x < 0. \end{matrix} \right \}$

#### Cumulative Distribution Function

$\large F(x ; \lambda ) = \left\{\begin{matrix} 1 – e^{-\lambda x} & x>= 0,\\ 0 & x < 0. \end{matrix}\right.$

where $\lambda > 0$ is called the rate of the distribution.

The mean of the Exponential ($\lambda$) Distribution is calculated using integration by parts as –

$\large E(X) = \int_{0}^{\infty } x\lambda e^{-\lambda x} \; dx$

$\large = \lambda \left [ \frac{-x \; e^{-\lambda x}}{\lambda}|_{0}^{\infty } + \frac{1}{\lambda }\int_{0}^{\infty } e^{-\lambda x} dx \right ]$

$\large = \lambda \left [ 0 + \frac{1}{\lambda }\frac{-e^{-\lambda x}}{\lambda} |_{o}^{\infty }\right ]$

$\large = \lambda \frac{1}{\lambda ^{2} }$

$\large = \frac{1}{\lambda }$

#### Practise This Question

Mendel used true breeding pea lines for his experiments because -