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A deck of 52 playing cards, containing all 4 aces, is randomly divided into 4 piles of 13 cards each. Define events \(E_{1}, E_{2}, E_{3}\), and \(E_{4}\) as follows: \(E_{1}=\\{\) the first pile has exactly 1 ace \(\\}\), \(E_{2}=\\{\) the second pile has exactly 1 ace \(\\}\), \(E_{3}=\\{\) the third pile has exactly 1 ace \(\\}\), \(E_{4}=\\{\) the fourth pile has exactly 1 ace \(\\}\) Use Exercise 23 to find \(P\left(E_{1} E_{2} E_{3} E_{4}\right)\), the probability that each pile has an ace.

Short Answer

Expert verified
The probability for each of the events \(E_1\), \(E_2\), \(E_3\), and \(E_4\) is the same and can be calculated as: \( P(E_i) = \frac{\bigl(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\bigr)}{\frac{52!}{(13!)^4}}\: (i = 1, 2, 3,\: or\: 4)\)

Step by step solution

01

Analyze the events E1, E2, E3, and E4

Since we have a random deck of 52 cards, with 4 aces, and we want to find the probability of each event, we will analyze events E1, E2, E3 and E4 as follows: \(E_1\) means exactly 1 Ace in the first pile, and the probability of this event occurring can be written as \(P(E_1)\). Similarly, we can write the probabilities for events E2, E3, and E4 as \(P(E_2)\), \(P(E_3)\), and \(P(E_4)\), respectively.
02

Calculate the total number of possible outcomes

To find the total number of possible outcomes, let's consider the fact that there are 52 cards, which we have to distribute into 4 piles (13 cards in each pile). Using the multinomial coefficient formula, we can calculate the total number of outcomes: Total number of outcomes \(= \frac{52!}{(13!)^4}\)
03

Calculate the number of favorable outcomes for each event

Now, let's calculate the number of favorable outcomes for each event: For \(E_1\), there are 12 non-ace cards left to be chosen for pile 1, which can be selected in \(\binom{48}{12}\) ways. After this, the remaining 40 cards can be distributed into the other 3 piles in \(\frac{40!}{(13!)^3}\) ways. Therefore, the number of possible ways for \(E_1\) is \(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\). Similarly, we can calculate the possible ways of events E2, E3 and E4: - For \(E_2\): \(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\) - For \(E_3\): \(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\) - For \(E_4\): \(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\)
04

Calculate the probability for each event

Now that we have calculated the number of possible outcomes and favorable outcomes for each event, we can calculate the probability for each event: - \( P(E_1) = \frac{\bigl(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\bigr)}{\frac{52!}{(13!)^4}}\) - \( P(E_2) = \frac{\bigl(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\bigr)}{\frac{52!}{(13!)^4}}\) - \( P(E_3) = \frac{\bigl(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\bigr)}{\frac{52!}{(13!)^4}}\) - \( P(E_4) = \frac{\bigl(\binom{48}{12} \cdot \frac{40!}{(13!)^3}\bigr)}{\frac{52!}{(13!)^4}}\) As the numerators are the same for all the events, we can conclude that all 4 events have the same probability. Calculate the probability for any of the events, and that will be true for all other events as well.

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Most popular questions from this chapter

Suppose that 5 percent of men and \(0.25\) percent of women are color-blind. A colorblind person is chosen at random. What is the probability of this person being male? Assume that there is an equal number of males and females.

Let \(E\) and \(F\) be mutually exclusive events in the sample space of an experiment. Suppose that the experiment is repeated until either event \(E\) or event \(F\) occurs. What does the sample space of this new super experiment look like? Show that the probability that event \(E\) occurs before event \(F\) is \(P(E) /[P(E)+P(F)]\). Hint: Argue that the probability that the original experiment is performed \(n\) times and \(E\) appears on the \(n\) th time is \(P(E) \times(1-p)^{n-1}, n=1,2, \ldots\), where \(p=P(E)+\) \(P(F)\). Add these probabilities to get the desired answer.

Suppose that \(P(E)=0.6 .\) What can you say about \(P(E \mid F)\) when (a) \(E\) and \(F\) are mutually exclusive? (b) \(E \subset F ?\) (c) \(F \subset E ?\)

There are three coins in a box. One is a two-headed coin, another is a fair coin, and the third is a biased coin that comes up heads 75 percent of the time. When one of the three coins is selected at random and flipped, it shows heads. What is the probability that it was the two-headed coin?

Stores \(A, B\), and \(C\) have 50,75, and 100 employees, and, respectively, 50,60, and 70 percent of these are women. Resignations are equally likely among all employees, regardless of sex. One employee resigns and this is a woman. What is the probability that she works in-store \(C\)?

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