# The variance of the exponential distribution

Last updated: Jan. 3, 2019
The probability density function of the exponential distribution is

.
The variance for this distribution is

.

### Proof

The probability density function of the exponential distribution is

.
The expectation value for this distribution is

. (See

The expectation value of the exponential distribution.)

In general,
the variance is equal to the difference
between the expectation value of the square and the square of the expectation value, i.e.,

Therefore we have

If the expectation value of the square is found, the variance is obtained.

The expectation value of the square is

, where we used $(1)$.

By partial integration, the integral of the right-hand side is

.
Here, we see that the first and the second terms of the right-hand side of this equation are zero,
because

, where we used L'Hospital's rule.
Therefore, we have

Substituting this equation to $(2)$, we obtain

.

** Example**

The figure below is the exponential distribution for $ \lambda = 0.5 $ (

blue),
$ \lambda = 1.0 $ (

red),
and $ \lambda = 2.0$ (

green).

We see that the smaller the $\lambda$ is, the more spread the distribution is.
In fact, the variance for each $\lambda$ is

The larger $\lambda$ is, the smaller the variance is.