Duplicate Question
The question on this page has been marked as a duplicate question.
Original Question
Suppose that X, Y, and Z are independent random variables with unit variance. Furthermore, E[X] )= 0 and E[Y] = E[Z]. Then, wha...Asked by silly_muffin
Suppose that X, Y, and Z are independent random variables with unit variance. Furthermore, E[X] )= 0 and E[Y] = E[Z] = 2. Then, what's the covariance of XY and XZ?
Answers
There are no human answers yet.
Answered by
Bot
To find the covariance of XY and XZ, we need to use the formula for covariance:
Cov(XY, XZ) = E[(XY)(XZ)] - E[XY]E[XZ]
First, let's calculate E[(XY)(XZ)]. Since X, Y, and Z are independent, we can multiply their expected values to get the expected value of the product:
E[(XY)(XZ)] = E[X^2 YZ]
Since X, Y, and Z have unit variance, E[X^2] = var(X) + E[X]^2 = 1 + 0^2 = 1. Therefore,
E[(XY)(XZ)] = E[X^2 YZ] = E[X^2]E[YZ] = 1 * E[YZ]
Next, let's calculate E[YZ]. Since Y and Z are independent, their expected value is equal to the product of their individual expected values:
E[YZ] = E[Y]E[Z]
Given that E[Y] = E[Z] = 2, we have:
E[YZ] = E[Y]E[Z] = 2 * 2 = 4
Now we can substitute these values into the covariance formula:
Cov(XY, XZ) = E[(XY)(XZ)] - E[XY]E[XZ]
= E[X^2 YZ] - E[XY]E[XZ]
= 1 * 4 - E[XY]E[XZ]
Since X, Y, and Z are independent, E[XY] = E[X]E[Y], and E[XZ] = E[X]E[Z]. Substituting these values:
Cov(XY, XZ) = 4 - E[X]E[Y]E[X]E[Z]
= 4 - 0 * 2 * 0 * 2
= 4
Therefore, the covariance of XY and XZ is 4.
Cov(XY, XZ) = E[(XY)(XZ)] - E[XY]E[XZ]
First, let's calculate E[(XY)(XZ)]. Since X, Y, and Z are independent, we can multiply their expected values to get the expected value of the product:
E[(XY)(XZ)] = E[X^2 YZ]
Since X, Y, and Z have unit variance, E[X^2] = var(X) + E[X]^2 = 1 + 0^2 = 1. Therefore,
E[(XY)(XZ)] = E[X^2 YZ] = E[X^2]E[YZ] = 1 * E[YZ]
Next, let's calculate E[YZ]. Since Y and Z are independent, their expected value is equal to the product of their individual expected values:
E[YZ] = E[Y]E[Z]
Given that E[Y] = E[Z] = 2, we have:
E[YZ] = E[Y]E[Z] = 2 * 2 = 4
Now we can substitute these values into the covariance formula:
Cov(XY, XZ) = E[(XY)(XZ)] - E[XY]E[XZ]
= E[X^2 YZ] - E[XY]E[XZ]
= 1 * 4 - E[XY]E[XZ]
Since X, Y, and Z are independent, E[XY] = E[X]E[Y], and E[XZ] = E[X]E[Z]. Substituting these values:
Cov(XY, XZ) = 4 - E[X]E[Y]E[X]E[Z]
= 4 - 0 * 2 * 0 * 2
= 4
Therefore, the covariance of XY and XZ is 4.
Submit Your Answer
We prioritize human answers over AI answers.
If you are human, and you can answer this question, please submit your answer.