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A coin is to be tossed until a head appears twice in a row. What is the sample space for this experiment? If the coin is fair, what is the probability that it will be tossed exactly four times?

Short Answer

Expert verified
The sample space for tossing a coin until a head appears twice in a row consists of infinite possible sequences like HH, THH, TTHH, TTTHH, and so on. For a fair coin, the probability of tossing it exactly four times until two consecutive heads appear, i.e., TTHH, is \(\frac{1}{16}\).

Step by step solution

01

Identify the sample space of the experiment

To identify the sample space of tossing a coin until we get two heads in a row, we need to consider all the possible sequences of flips that result in two consecutive heads. The sequences can be of different lengths, but they must end in two consecutive heads. Here are the possible sequences: - HH - THH - TTHH - TTTHH, and so on. As we can see, for each additional 'T' in the sequence, the length of the sequence increases by 1. Since there's no upper bound on the length, the sample space is infinite.
02

Determine the probability of each outcome for a fair coin

Now that we have identified the sample space of the experiment, we need to determine the probability of each possible outcome for a fair coin. A fair coin has a probability of 1/2 for heads and 1/2 for tails. For example, the probability of the first outcome, HH, is (\(\frac{1}{2}\))^2 = \(\frac{1}{4}\). To generalize the probability for any sequence with k tails followed by two heads, we can use the following formula: P(k tails followed by two heads) = (\(\frac{1}{2}\))^(k + 2) Here, k + 2 refers to the total number of tosses in the sequence.
03

Calculate the probability of tossing the coin exactly four times

Now that we have determined the probability of each outcome for a fair coin, we need to find the probability of tossing the coin exactly four times. In this case, our sequence looks like TTHH, which has 2 tails followed by two heads. To find this probability, we can plug k = 2 in the formula from Step 2: P(2 tails followed by two heads) = (\(\frac{1}{2}\))^(2 + 2) = (\(\frac{1}{2}\))^4 = \(\frac{1}{16}\) Thus, the probability of tossing a fair coin exactly four times until two consecutive heads appear is \(\frac{1}{16}\).

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Most popular questions from this chapter

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.

Show that $$ P\left(\bigcup_{i=1}^{n} E_{i}\right) \leqslant \sum_{i=1}^{n} P\left(E_{i}\right) $$ This is known as Boole's inequality. Hint: Either use Equation (1.2) and mathematical induction, or else show that \(\bigcup_{i=1}^{n} E_{i}=\bigcup_{i=1}^{n} F_{i}\), where \(F_{1}=E_{1}, F_{i}=E_{i} \bigcap_{j=1}^{i-1} E_{j}^{c}\), and use property (iii) of a probability.

Sixty percent of the families in a certain community own their own car, thirty percent own their own home, and twenty percent own both their own car and their own home. If a family is randomly chosen, what is the probability that this family owns a car or a house but not both?

Let \(E, F, G\) be three events. Find expressions for the events that of \(E, F, G\) (a) only \(F\) occurs, (b) both \(E\) and \(F\) but not \(G\) occur, (c) at least one event occurs, (d) at least two events occur, (e) all three events occur, (f) none occurs, (g) at most one occurs, (h) at most two occur.

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.

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