C2. Let X and Y be random variables, and let a and b be constants. (a) Starting from the definition of covariance, show that Cov(aX,Y)= a Cov(X, Y). You may find it helpful to remember that if EX = x, then EaX = aux. (b) Show that Cov(X+b, Y) = Cov(X, Y). Now let X, Y, Z be independent random variables with common variance o². (c) Find the value of Corr(2X-3Y+4, 2Y - Z-1). You may use any facts about covariance from the notes, including those from parts (a) and (b) of this question, provided you state them clearly.

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C2. Let X and Y be random variables, and let a and b be constants.
(a) Starting from the definition of covariance, show that Cov(aX, Y): = a Cov(X, Y). You may find
it helpful to remember that if EX = µx, then EaX = αμχ·
(b) Show that Cov(X + b, Y) = Cov(X, Y).
Now let X, Y, Z be independent random variables with common variance o².
(c) Find the value of Corr(2X - 3Y + 4, 2Y – Z - 1). You may use any facts about covariance from
the notes, including those from parts (a) and (b) of this question, provided you state them clearly.
Transcribed Image Text:C2. Let X and Y be random variables, and let a and b be constants. (a) Starting from the definition of covariance, show that Cov(aX, Y): = a Cov(X, Y). You may find it helpful to remember that if EX = µx, then EaX = αμχ· (b) Show that Cov(X + b, Y) = Cov(X, Y). Now let X, Y, Z be independent random variables with common variance o². (c) Find the value of Corr(2X - 3Y + 4, 2Y – Z - 1). You may use any facts about covariance from the notes, including those from parts (a) and (b) of this question, provided you state them clearly.
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