Nominal distribution?

A nominal distribution is a type of statistical distribution that represents the frequency of different categories or groups in a dataset. It is used to describe the distribution of categorical data, where the categories do not have a natural order or ranking. Examples of nominal distributions include the distribution of eye colors, types of cars, or political affiliations in a population.

A nominal distribution is a probability distribution of a discrete random variable that takes on a finite number of values. The values of the random variable are typically unordered and non-numeric, and represent different categories or labels.

For example, a nominal distribution could represent the distribution of genders in a population, with the possible values being "male" and "female". Another example could be the distribution of blood types in a population, with the possible values being "A", "B", "AB", and "O".

The probability mass function of a nominal distribution is given by:

```
P(X = x) = p_x
```

where x is one of the possible values of the random variable, and p_x is the probability of observing that value.

The sum of the probabilities of all possible values must equal 1:

```
∑ p_x = 1
```

Nominal distributions are often used in statistical analysis to represent categorical data. They can be used to compare the proportions of different categories in a population, or to test for differences between groups.