In this issue, I will talk about different distributions and their use.
TL;DR
- Binomial distribution presents the number of successes for different random experiments.
- Beta distribution presents the probability of an event. The result is bounded between 0 and 1.
- Poisson distribution is helpful when you want to model events that occur during a period of time.
- Gamma distribution is used to model continuous probability distributions.
Binomial distribution
Discrete or continuous values
Discrete
Example of use
Conversion on a website.
You convert or you don’t. It’s a success or a failure. This is what binomial distribution is about.
Beta distribution
Discrete or continuous values
Continuous
Example of use
Useful to model the prior probability distribution when doing ABTests with binomial distribution. There are two parameters: alpha is the successes, beta is the failures
Links
Poisson distribution
Discrete or continuous values
Discrete
Example of use
Goals during a football match.
The period of time is the match. The number of goals are the events.
Link
Better Know a Distribution: The Poisson Distribution
Gamma distribution
Discrete or continuous values
Continuous
Example of use
Useful to model the prior probability distribution when doing ABTests with binomial distribution. There are two parameters: alpha is the occurrences for a period of time, beta is the number of periods of time.
Links
Thank you for reading. Feel free to contact me on Twitter if you want to discuss that.