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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?

Short Answer

Expert verified
The probability that it was the two-headed coin, given that the coin flip shows heads, is \(\frac{4}{11}\) or approximately 0.36.

Step by step solution

01

Identify the probabilities

Let's identify the probabilities we know: - The probability of selecting each coin: P(A) = P(B) = P(C) = 1/3 - The probability of getting heads from the two-headed coin (Coin A): P(Heads|A) = 1 - The probability of getting heads from the fair coin (Coin B): P(Heads|B) = 1/2 - The probability of getting heads from the biased coin (Coin C): P(Heads|C) = 3/4
02

Use the conditional probability formula

The formula for finding the conditional probability is: P(A|Heads) = P(Heads and A) / P(Heads)
03

Find the probability of Heads

To find the probability of getting heads, we can use the law of total probability: P(Heads) = P(Heads|A) * P(A) + P(Heads|B) * P(B) + P(Heads|C) * P(C) Plugging in the values we have: P(Heads) = (1) * (1/3) + (1/2) * (1/3) + (3/4) * (1/3) = 1/3 + 1/6 + 1/4 = 11/12
04

Find the probability of Heads and A

Since Coin A is a two-headed coin, the probability of selecting it and flipping heads is the same as the probability of selecting Coin A: P(Heads and A) = P(A) = 1/3
05

Calculate the conditional probability

Now we can plug the values we found into the conditional probability formula: P(A|Heads) = (1/3) / (11/12) Multiply the numerator and denominator by 12 to get rid of the fraction: P(A|Heads) = (4) / (11) So, the probability that the coin selected is the two-headed coin (Coin A) given that the coin flip shows heads is 4/11 or approximately 0.36.

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Most popular questions from this chapter

(a) A gambler has in his pocket a fair coin and a two-headed coin. He selects one of the coins at random, and when he flips it, it shows heads. What is the probability that it is a fair coin? (b) Suppose that he flips the same coin a second time and again it shows heads. Now, what is the probability that it is a fair coin? (c) Suppose that he flips the same coin a third time and it shows tails. Now, what is the probability that it is a fair coin?

In an election, candidate \(A\) receives \(n\) votes and candidate \(B\) receives \(m\) votes, where \(n>m .\) Assume that in the count of the votes all possible orderings of the \(n+m\) votes are equally likely. Let \(P_{n, m}\) denote the probability that from the first vote on \(A\) is always in the lead. Find (a) \(P_{2,1}\) (b) \(P_{3,1}\) (c) \(P_{n, 1}\) (d) \(P_{3,2}\) (e) \(P_{4,2}\) (f) \(P_{n, 2}\) (g) \(P_{4,3}\) (h) \(P_{5,3}\) (i) \(P_{5,4}\) (j) Make a conjecture as to the value of \(P_{n, m}\).

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 all \(n\) men at a party throw their hats in the center of the room. Each man then randomly selects a hat. Show that the probability that none of the \(n\) men selects his own hat is $$ \frac{1}{2 !}-\frac{1}{3 !}+\frac{1}{4 !}-+\cdots \frac{(-1)^{n}}{n !} $$ Note that as \(n \rightarrow \infty\) this converges to \(e^{-1}\). Is this surprising?

Use Exercise 15 to show that \(P(E \cup F)=P(E)+P(F)-P(E F)\).

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