What is the Gamma Distribution Used For?

An intuitive example to understand the Gamma and how it can be used

The Gamma distribution is a continuous probability distribution that is often used to model the amount of time until a certain number of events occur. It is related to the Exponential and Binomial distributions. In order to understand the Gamma intuitively let’s start off with a simple Bernoulli example.

The Bernoulli distribution models any “success/failure” scenario.

Let’s say you’re at the airport watching some landing track and you want to model the following experiment: whether the next plane is going to land before the following 120 seconds or after (I’m tired of the coin toss example), being a success if the plane lands before and failure otherwise:

X ~ Bernoulli(p)

*Note: The Bernoulli distribution only depends on 1 parameter “p” which in the current context is the probability of plane landing under 120 s.

Now, let’s say you want to model this experiment but for all of the 10 tracks on the airport. Then you can use the Binomial distribution which is simply “many Bernoulli trials”, and you can model how many planes are going to land before 120 seconds on 10 different tracks:

X ~ Binomial(p, n)

*Note: The Binomial distribution takes 2 parameters; “p” which is the same as the Bernoulli and “n” which would be the number of trials (landing tracks). In…