Suppose that X1, X2, and X3 are independent random variables. Suppose further that E(X1) = 4 E(X2) = 5 E(X3) = 7 and Var(X1) = 4 Var(X2) Var(X3) = v2 a.) Compute E(4X1 +«X2 + eX3+13) b.) Compute E(X1X3 + X2) c.) Compute Var(V2X2+ V3X3+17)

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**Example Problem on Expected Value and Variance of Linear Combinations of Independent Random Variables**

**Problem Statement:**

Suppose that \(X_1, X_2,\) and \(X_3\) are independent random variables. Suppose further that
\[ E(X_1) = 4 \]
\[ E(X_2) = 5 \]
\[ E(X_3) = 7 \]

and
\[ Var(X_1) = 4 \]
\[ Var(X_2) = \frac{1}{2} \]
\[ Var(X_3) = \sqrt{2} \]

(**Tasks**)

a.) Compute \( E(4X_1 + \pi X_2 + e X_3 + 13) \)

b.) Compute \( E(X_1 X_3 + X_2) \)

c.) Compute \( Var(\sqrt{2} X_2 + \sqrt{3} X_3 + 17) \)

### Solutions:

**a.) Compute \( E(4X_1 + \pi X_2 + e X_3 + 13) \)**

To find the expectation of a linear combination of random variables, we use the linearity property of expectation:

\[ E(aX + bY + c) = aE(X) + bE(Y) + c \]

Thus for the given expression:

\[ E(4X_1 + \pi X_2 + e X_3 + 13) = 4E(X_1) + \pi E(X_2) + e E(X_3) + 13 \]
\[ E(4X_1 + \pi X_2 + e X_3 + 13) = 4(4) + \pi(5) + e(7) + 13 \]
\[ E(4X_1 + \pi X_2 + e X_3 + 13) = 16 + 5\pi + 7e + 13 \]
\[ E(4X_1 + \pi X_2 + e X_3 + 13) = 29 + 5\pi + 7e \]

**b.) Compute \( E(X_1 X_3 + X_2) \)**

For the second expectation, we must note that expectation of the product of independent random variables is the product of expectations:
Transcribed Image Text:**Example Problem on Expected Value and Variance of Linear Combinations of Independent Random Variables** **Problem Statement:** Suppose that \(X_1, X_2,\) and \(X_3\) are independent random variables. Suppose further that \[ E(X_1) = 4 \] \[ E(X_2) = 5 \] \[ E(X_3) = 7 \] and \[ Var(X_1) = 4 \] \[ Var(X_2) = \frac{1}{2} \] \[ Var(X_3) = \sqrt{2} \] (**Tasks**) a.) Compute \( E(4X_1 + \pi X_2 + e X_3 + 13) \) b.) Compute \( E(X_1 X_3 + X_2) \) c.) Compute \( Var(\sqrt{2} X_2 + \sqrt{3} X_3 + 17) \) ### Solutions: **a.) Compute \( E(4X_1 + \pi X_2 + e X_3 + 13) \)** To find the expectation of a linear combination of random variables, we use the linearity property of expectation: \[ E(aX + bY + c) = aE(X) + bE(Y) + c \] Thus for the given expression: \[ E(4X_1 + \pi X_2 + e X_3 + 13) = 4E(X_1) + \pi E(X_2) + e E(X_3) + 13 \] \[ E(4X_1 + \pi X_2 + e X_3 + 13) = 4(4) + \pi(5) + e(7) + 13 \] \[ E(4X_1 + \pi X_2 + e X_3 + 13) = 16 + 5\pi + 7e + 13 \] \[ E(4X_1 + \pi X_2 + e X_3 + 13) = 29 + 5\pi + 7e \] **b.) Compute \( E(X_1 X_3 + X_2) \)** For the second expectation, we must note that expectation of the product of independent random variables is the product of expectations:
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