Definition: Let $A$ and $B$ be two arbitrary statements about random variables, such as statements about the presence or absence of an event or about the value of a scalar, vector or matrix. Then, $p(A,B)$ is called the joint probability of $A$ and $B$ and is defined as the probability that $A$ and $B$ are both true.
- Wikipedia (2020): "Joint probability distribution" ; in: Wikipedia, the free encyclopedia , retrieved on 2020-05-10 ; URL: https://en.wikipedia.org/wiki/Joint_probability_distribution .
- Jason Browlee (2019): "A Gentle Introduction to Joint, Marginal, and Conditional Probability" ; in: Machine Learning Mastery , retrieved on 2021-08-01 ; URL: https://machinelearningmastery.com/joint-marginal-and-conditional-probability-for-machine-learning/ .
Metadata: ID: D49 | shortcut: prob-joint | author: JoramSoch | date: 2020-05-10, 19:49.