HHH \(\to 0\)
HHT \(\to 0\)
HTH \(\to 1\)
HTT \(\to 0\)
THH \(\to 1\)
THT \(\to 1\)
TTH \(\to 1\)
TTT \(\to 0\)
Probability distribution:
\[ \mu = \sum x_i P_i = \frac{1}{2} \] \[ \sigma^2 = \sum x_i^2 P_i - \mu^2 = \frac{1}{2} \times 1^2 + \frac{1}{2} \times 1^2 - \left(\frac{1}{2}\right)^2 = \frac{1}{4} \] \[ 64(\mu + \sigma^2) = 64\left(\frac{1}{2} + \frac{1}{4}\right) = 64 \times \frac{3}{4} = 48 \]
Given: A coin is tossed three times. Let \( X \) = number of times a Tail follows a Head. We need to find \( 64(\mu + \sigma^2) \), where \( \mu = E(X) \) and \( \sigma^2 = Var(X) \).
Step 1: List all possible outcomes Total outcomes = \( 2^3 = 8 \) | Outcome | X (Tail follows Head) | |----------|-----------------------| | HHH | 0 | | HHT | 1 | | HTH | 1 | | HTT | 1 | | THH | 0 | | THT | 1 | | TTH | 0 | | TTT | 0 |
Step 2: Compute frequencies \( X = 0 \) occurs in 4 cases. \( X = 1 \) occurs in 4 cases. So, \( P(X=0) = \frac{4}{8} = \frac{1}{2} \) \( P(X=1) = \frac{4}{8} = \frac{1}{2} \)
Step 3: Mean \[ \mu = E(X) = 0\cdot\frac{1}{2} + 1\cdot\frac{1}{2} = \frac{1}{2} \]
Step 4: Variance \[ E(X^2) = 0^2\cdot\frac{1}{2} + 1^2\cdot\frac{1}{2} = \frac{1}{2} \] \[ \sigma^2 = E(X^2) - [E(X)]^2 = \frac{1}{2} - \left(\frac{1}{2}\right)^2 = \frac{1}{4} \]
Step 5: Compute required value \[ 64(\mu + \sigma^2) = 64\left(\frac{1}{2} + \frac{1}{4}\right) = 64\left(\frac{3}{4}\right) = 48 \]
∴ Correct option: 2) 48
The probability distribution of the random variable X is given by
| X | 0 | 1 | 2 | 3 |
|---|---|---|---|---|
| P(X) | 0.2 | k | 2k | 2k |
Find the variance of the random variable \(X\).