Editing Marginal distribution (section)

=== Definition ===
The '''marginal probability''' is the probability of a single event occurring, independent of other events. A '''[[Conditional probability distribution|conditional probability]]''', on the other hand, is the probability that an event occurs given that another specific event ''has already'' occurred. This means that the calculation for one variable is dependent on another variable.<ref>{{Cite web|url=https://study.com/academy/lesson/marginal-conditional-probability-distributions-definition-examples.html|title=Marginal & Conditional Probability Distributions: Definition & Examples|website=Study.com|language=en|access-date=2019-11-16}}</ref>

The conditional distribution of a variable given another variable is the joint distribution of both variables divided by the marginal distribution of the other variable.<ref>{{Cite web|url=https://www.math.fsu.edu/~paris/Pexam/|title=Exam P [FSU Math]|website=www.math.fsu.edu|access-date=2019-11-16}}</ref> That is,

* For '''discrete [[random variable]]s''',<math display="block">p_{Y|X}(y|x) = P(Y=y \mid X=x) = \frac{P(X=x,Y=y)}{P_X(x)}</math>
* For '''continuous random variables''',<math display="block">f_{Y|X}(y|x)=\frac{f_{X,Y}(x,y)}{f_X(x)}</math>