Let X be a random variable. Let E (X) and Var (X) denote the mean and the variance of X respectively. Then match List-I with List-II
List-I List-II (A) If Var (X) = , then Var (2X + 3) is (I) 11 (B) If E (X) = , then E (2X) is (II) 6 (C) If Var (X) = , then Var(3X - ) + Var () is (III) 4 (D) If E (X) = , then E (12X + ) is (IV) 2
Choose the correct answer from the options given below:
Let X be a random variable. Let E (X) and Var (X) denote the mean and the variance of X respectively. Then match List-I with List-II
| List-I | List-II |
|---|---|
| (A) If Var (X) = , then Var (2X + 3) is | (I) 11 |
| (B) If E (X) = , then E (2X) is | (II) 6 |
| (C) If Var (X) = , then Var(3X - ) + Var () is | (III) 4 |
| (D) If E (X) = , then E (12X + ) is | (IV) 2 |
Choose the correct answer from the options given below:
Solution
For Expectation: E(aX + b) = a·E(X) + b
For Variance: Var(aX + b) = a²·Var(X), where constants vanish in variance calculations.
(A) If Var(X) = , then Var(2X + 3) is
The coefficient of X is 2.
Var(2X + 3) =
Match: (A) → (III)
(B) If E(X) = , then E(2X) is
E(2X) =
Match: (B) → (IV)
(C) If Var(X) = , then Var(3X - ) + Var() is
The constant vanishes in variance:
Var(3X - ) =
The constant vanishes in variance:
Var() =
Total =
Match: (C) → (I)
(D) If E(X) = , then E(12X + ) is
E(12X + ) =
Match: (D) → (II)
Therefore, the correct matching is:
(A) - (III), (B) - (IV), (C) - (I), (D) - (II)
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