Discrete Uniform - each of a finite collection of outcomes is equally likely and prescribed a "position" and \(X\) measures the position of an item selected randomly from the outcomes.

Continuous Uniform - an interval of values is possible with sub-intervals of equal length having equal probabilities and \(X\) measures a location inside that interval.

Hypergeometric - each of a finite collection of values are equally likely and grouped into two classes (successes vs failures) and a subset of that collection is extracted with \(X\) measuring the number of successes in the sample.