Cov(X,Y) = E[(X - E[X])(Y - E[Y])] = E[XY] - E[X]E[Y]. Correlation: ρ = Cov(X,Y) / (σ_X · σ_Y). Correlation is bounded: -1 ≤ ρ ≤ 1. ρ = ±1 indicates linear relationship.
Multiple Discrete Random Variables
View .mdCov(X,Y) = E[(X - E[X])(Y - E[Y])] = E[XY] - E[X]E[Y]. Correlation: ρ = Cov(X,Y) / (σ_X · σ_Y). Correlation is bounded: -1 ≤ ρ ≤ 1. ρ = ±1 indicates linear relationship.