When calculating the expectation of an event involving multiple independent trials (like rolling dice), the total expectation is simply the sum of the individual expectations. For each die, the expectation is the probability of getting the event (in this case, rolling a four), and since the dice rolls are independent, we can just add the expectations together.
The probability of any single die showing a four is \( \frac{1}{6} \). The expected value of \( X \), representing the total count of fours, is calculated by summing the individual expectations for each die:
\[ E(X) = E(X_1) + E(X_2), \]
given that:
\[ E(X_1) = \frac{1}{6}, \quad E(X_2) = \frac{1}{6}. \]
Therefore:
\[ E(X) = \frac{1}{6} + \frac{1}{6} = \frac{2}{6} = \frac{1}{3}. \]
If \(S=\{1,2,....,50\}\), two numbers \(\alpha\) and \(\beta\) are selected at random find the probability that product is divisible by 3 :
The probability of hitting the target by a trained sniper is three times the probability of not hitting the target on a stormy day due to high wind speed. The sniper fired two shots on the target on a stormy day when wind speed was very high. Find the probability that
(i) target is hit.
(ii) at least one shot misses the target. 