\( \frac{1}{13} \)
Step 1: Define the Probability Distribution
A standard deck of playing cards consists of 52 cards, out of which 4 are aces. The probability of drawing an ace in a single draw is: \[ P(A) = \frac{4}{52} = \frac{1}{13} \] Since the draws are done with replacement, the probability of drawing an ace remains constant for both draws.
Step 2: Define the Random Variable \( X \)
The random variable \( X \) represents the number of aces drawn in two independent trials. Since each draw is independent and follows a Bernoulli process, \( X \) follows a binomial distribution: \[ X \sim \text{Binomial}(n=2, p=\frac{1}{13}) \] where: - \( n = 2 \) (two trials), - \( p = \frac{1}{13} \) (probability of success in a single trial).
Step 3: Compute the Expected Value (Mean)
The mean of a binomial distribution is given by: \[ E(X) = n p \] Substituting values: \[ E(X) = 2 \times \frac{1}{13} = \frac{2}{13} \]
Step 4: Conclusion
Thus, the mean of the probability distribution of \( X \) is: \[ \mathbf{\frac{2}{13}} \]
A shop selling electronic items sells smartphones of only three reputed companies A, B, and C because chances of their manufacturing a defective smartphone are only 5%, 4%, and 2% respectively. In his inventory, he has 25% smartphones from company A, 35% smartphones from company B, and 40% smartphones from company C.
A person buys a smartphone from this shop
A shop selling electronic items sells smartphones of only three reputed companies A, B, and C because chances of their manufacturing a defective smartphone are only 5%, 4%, and 2% respectively. In his inventory, he has 25% smartphones from company A, 35% smartphones from company B, and 40% smartphones from company C.
A person buys a smartphone from this shop
(i) Find the probability that it was defective.
Match the following: