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\(A, B\), and \(C\) are evenly matched tennis players. Initially \(A\) and \(B\) play a set, and the winner then plays \(C\). This continues, with the winner always playing the waiting player, until one of the players has won two sets in a row. That player is then declared the overall winner. Find the probability that \(A\) is the overall winner.

Short Answer

Expert verified
The probability that A is the overall winner is \(0.375\) or \(37.5\%\).

Step by step solution

01

Define The Probabilities

Each set has a 50% chance for each player to win, so let's denote this for our calculations. - Probability of A winning = \(P(A) = 0.5\) - Probability of B winning = \(P(B) = 0.5\) - Probability of C winning = \(P(C) = 0.5\)
02

Create a Probability Tree

Let's create a probability tree with the possible outcomes of the game. Start with the first set where A plays against B. 1. A vs. B: There are 2 possible outcomes-A wins or B wins. Now, we'll consider possible outcomes when the winner plays against C. 2. If A wins the first set: a. A vs. C: A wins or C wins b. If A wins two sets in a row, A is the overall winner. c. If C wins, the game proceeds with C vs. B. 3. If B wins the first set: a. B vs. C: B wins or C wins b. If B wins two sets in a row, B is the overall winner. c. If C wins, the game proceeds with C vs. A. Now that we have all the possible outcomes, we can derive a condition for A winning the game.
03

Define the Condition for A Winning

A can only win the game in one of the following scenarios: 1. A wins two sets in a row: A beats B and then A beats C. 2. C wins a set after B: C beats B and then A beats C.
04

Calculate the Probability for Each Scenario

1. Probability of A winning two sets in a row: - \(P(A \: wins \: two \: in \: a \: row) = P(A \: beats \: B) * P(A \: beats \: C) = 0.5 * 0.5 = 0.25\) 2. Probability of C winning a set after B and then A winning: - \(P(C \: wins \: after \: B \: and \: A \: wins) = P(A \: loses \: to \: B) * P(C \: beats \: B) * P(A \: beats\: C) = 0.5 * 0.5 * 0.5 = 0.125\)
05

Calculate the Total Probability for A Winning

Now let's sum up the probabilities from both scenarios: \(P(A \: is \: overall \: winner) = P(A \: wins \: two \: in \: a \: row) + P(C \: wins \: after \: B \: and \: A \: wins) = 0.25 + 0.125 = 0.375\) So, the probability that A is the overall winner is 0.375 or 37.5%.

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Most popular questions from this chapter

A coin having probability \(p\) of coming up heads is successively flipped until two of the most recent three flips are heads. Let \(N\) denote the number of flips. (Note that if the first two flips are heads, then \(N=2 .\) ) Find \(E[N]\).

Independent trials, each resulting in success with probability \(p\), are performed. (a) Find the expected number of trials needed for there to have been both at least \(n\) successes or at least \(m\) failures. Hint: Is it useful to know the result of the first \(n+m\) trials? (b) Find the expected number of trials needed for there to have been either at least \(n\) successes or at least \(m\) failures. Hint: Make use of the result from part (a).

Let \(X\) be exponential with mean \(1 / \lambda ;\) that is, $$ f_{X}(x)=\lambda e^{-\lambda x}, \quad 01]\)

A deck of \(n\) cards, numbered 1 through \(n\), is randomly shuffled so that all \(n !\) possible permutations are equally likely. The cards are then turned over one at a time until card number 1 appears. These upturned cards constitute the first cycle. We now determine (by looking at the upturned cards) the lowest numbered card that has not yet appeared, and we continue to turn the cards face up until that card appears. This new set of cards represents the second cycle. We again determine the lowest numbered of the remaining cards and turn the cards until it appears, and so on until all cards have been turned over. Let \(m_{n}\) denote the mean number of cycles. (a) Derive a recursive formula for \(m_{n}\) in terms of \(m_{k}, k=1, \ldots, n-1\). (b) Starting with \(m_{0}=0\), use the recursion to find \(m_{1}, m_{2}, m_{3}\), and \(m_{4}\). (c) Conjecture a general formula for \(m_{n}\). (d) Prove your formula by induction on \(n\). That is, show it is valid for \(n=1\), then assume it is true for any of the values \(1, \ldots, n-1\) and show that this implies it is true for \(n\). (e) Let \(X_{i}\) equal 1 if one of the cycles ends with card \(i\), and let it equal 0 otherwise, \(i=1, \ldots, n\). Express the number of cycles in terms of these \(X_{i}\). (f) Use the representation in part (e) to determine \(m_{n}\). (g) Are the random variables \(X_{1}, \ldots, X_{n}\) independent? Explain. (h) Find the variance of the number of cycles.

A coin, having probability \(p\) of landing heads, is continually flipped until at least one head and one tail have been flipped. (a) Find the expected number of flips needed. (b) Find the expected number of flips that land on heads. (c) Find the expected number of flips that land on tails. (d) Repeat part (a) in the case where flipping is continued until a total of at least two heads and one tail have been flipped.

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