Understanding data distributions
Although the Gaussian distribution is probably the most common distribution for statistical and machine learning models, you should be aware that it is not the only one. There are other types of data distributions, such as the Bernoulli, binomial, and Poisson distributions.
The Bernoulli distribution is a very simple one, as there are only two types of possible events: success or failure. The success event has a probability p of happening, while the failure one has a probability of 1-p.
Some examples that follow a Bernoulli distribution are rolling a six-sided die or flipping a coin. In both cases, you must define the event of success and the event of failure. For example, assume the following success and failure events when rolling a die:
- Success: Getting a number 6
- Failure: Getting any other number
You can then say that there is a p probability of success (1/6 = 0.16 = 16%) and a 1-p probability of failure (1 - 0.16 = 0.84...
