Grinstead-Snell-Probability · Problem 6.3.18

Sums of Random Variables

Mathematics · correlation

Problem

Let XX and YY be random variables with positive variance. The correlation of XX and YY is defined as ρ(X,Y)=cov(X,Y)V(X)V(Y) .\rho(X, Y) = \frac{\mathrm{cov}(X, Y)}{\sqrt{V(X)V(Y)}}\,. (a) Using Exercise 17(c), show that 0≤V ⁣(Xσ(X)+Yσ(Y))=2(1+ρ(X,Y)) .0 \leq V\!\left(\frac{X}{\sigma(X)} + \frac{Y}{\sigma(Y)}\right) = 2(1 + \rho(X, Y))\,. (b) Now show that 0≤V ⁣(Xσ(X)−Yσ(Y))=2(1−ρ(X,Y)) .0 \leq V\!\left(\frac{X}{\sigma(X)} - \frac{Y}{\sigma(Y)}\right) = 2(1 - \rho(X, Y))\,. (c) Using (a) and (b), show that −1≤ρ(X,Y)≤1 .-1 \leq \rho(X, Y) \leq 1\,.

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