Joint Probability Distribution

Joint probability distributions describe the likelihood of multiple random variables taking on specific values simultaneously. They capture dependencies between variables and can be used to derive marginal and conditional probabilities. The distribution can be represented as a table for discrete variables or as a multivariate function for continuous variables.

Pattern recognition, multivariate analysis, dependency modeling, risk assessment, and machine learning feature analysis.