if X and Y are random variables such that Var(X)<∞ and Var(Y)<∞,show that
Var(aX+bY)=a2Var(X)+b2Var(Y)+2ab cov(X,Y). Where a and b are real constants.
E[(aX+by)−(aμX+bμY)]2=E[a(X−μX)+b(Y−μY)]2=E[a(X−μX)]2+E[2ab(X−μX)(Y−μY)]+E[b(Y−μY)]2=a2Var(X)+2abCov(X,Y)+b2Var(Y)=a2Var(X)+b2Var(Y)+2abCov(X,Y)E{[(aX+by)-(aμ_X+bμ_Y )]^2 }=E{[a(X-μ_X )+b(Y-μ_Y )]^2 } \\=E{[a(X-μ_X )]^2 }+E{[2ab(X-μ_X )(Y-μ_Y )]}+E{[b(Y-μ_Y )]^2 } \\=a^2 \text{Var(X)}+2ab\text{Cov(X,Y)}+b^2 \text{Var(Y)} \\=a^2 \text{Var(X)}+b^2 \text{Var(Y)}+2ab\text{Cov(X,Y)}E[(aX+by)−(aμX+bμY)]2=E[a(X−μX)+b(Y−μY)]2=E[a(X−μX)]2+E[2ab(X−μX)(Y−μY)]+E[b(Y−μY)]2=a2Var(X)+2abCov(X,Y)+b2Var(Y)=a2Var(X)+b2Var(Y)+2abCov(X,Y)
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