QuestionFind given , , , .
Studdy Solution
STEP 1
Assumptions1. The expectation of X,(X), is6. The variance of X, Var(X), is13. The expectation of Y,(Y), is34. The variance of Y, Var(Y), is95. The correlation between X and Y, Corr(X, Y), is not given6. The covariance between X and Y, Cov(X, Y), is defined as[(X-E[X])(Y-E[Y])]
7. The variance of X, Var(X), is also defined as Cov(X, X)
STEP 2
We are asked to find the value of((X+2Y)^2). Let's first expand this expression.
STEP 3
Now, we apply the expectation operator to each term in the expanded expression.
STEP 4
We can simplify this further by taking the constants out of the expectation operator.
STEP 5
We know that(X^2) can be calculated as Var(X) + [(X)]^2, and(Y^2) can be calculated as Var(Y) + [(Y)]^2. Let's substitute these into the equation.
STEP 6
We also know that(XY) can be calculated as Cov(X, Y) +(X)(Y). Let's substitute this into the equation.
STEP 7
Now we can substitute the given values for(X), Var(X),(Y), and Var(Y) into the equation.
STEP 8
We don't have the value for Cov(X, Y), but we know that Cov(X, Y) = Corr(X, Y) * sqrt[Var(X) * Var(Y)]. Since Corr(X, Y) is not given, we can't calculate Cov(X, Y). But we know that Cov(X, Y) =0 if X and Y are independent. So, let's assume X and Y are independent and Cov(X, Y) =0.
STEP 9
Now, we can calculate the value of((X+2Y)^2).
So, the value of((X+2Y)^2) is181.
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