Question:

If the mean of the following probability distribution of a random variable \( X \): \[ \begin{array}{|c|c|c|c|c|c|} \hline X & 0 & 2 & 4 & 6 & 8 \\ \hline P(X) & a & 2a & a+b & 2b & 3b \\ \hline \end{array} \] is \( \frac{46}{9} \), then the variance of the distribution is:

Updated On: Nov 24, 2024
  • \( \frac{581}{81} \)
  • \( \frac{566}{81} \)
  • \( \frac{173}{27} \)
  • \( \frac{151}{27} \)
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The Correct Option is B

Solution and Explanation

1. From the given probability distribution, the total probability must equal 1:

\[ \sum P_i = 1 \implies a + 2a + a + b + 2b + 3b = 1. \]

Simplify:

\[ 4a + 6b = 1 \quad \cdots \text{(I)} \]

2. The mean is given by:

\[ E(X) = \sum P_i X_i = \frac{46}{9}. \]

Substitute the probabilities:

\[ E(X) = 0 \times a + 2 \times 2a + 4 \times (a + b) + 6 \times 2b + 8 \times 3b. \]

Simplify:

\[ 4a + 4b + 12b + 24b = \frac{46}{9}, \]

\[ 8a + 40b = \frac{46}{9} \quad \cdots \text{(II)}. \]

3. Solve equations (I) and (II) simultaneously: From (I): \(b = \frac{1}{9} - \frac{2a}{3}\). Substitute \(b = \frac{1}{9}\) and solve to find:

\[ a = \frac{1}{12}, \quad b = \frac{1}{9}. \]

4. Variance is calculated as:

\[ \text{Variance} = E(X^2) - (E(X))^2. \]

Step 1: Find \(E(X^2)\):

\[ E(X^2) = \sum P_i X_i^2 = 0^2 \times a + 2^2 \times 2a + 4^2 \times (a + b) + 6^2 \times 2b + 8^2 \times 3b. \]

Simplify:

\[ E(X^2) = 4a + 16(a + b) + 72b + 192b. \]

Substitute \(a = \frac{1}{12}, b = \frac{1}{9}\):

\[ E(X^2) = \frac{298}{9}. \]

Step 2: Find \((E(X))^2\):

\[ (E(X))^2 = \left(\frac{46}{9}\right)^2 = \frac{2116}{81}. \]

Step 3: Calculate variance:

\[ \text{Variance} = \frac{298}{9} - \frac{2116}{81} = \frac{566}{81}. \]

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