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Six people hope to be selected as a contestant on a TV game show. Two of these people are younger than 25 years old. Two of these six will be chosen at random to be on the show. a. What is the sample space for the chance experiment of selecting two of these people at random? (Hint: You can think of the people as being labeled \(\mathrm{A}, \mathrm{B}, \mathrm{C}, \mathrm{D}, \mathrm{E},\) and \(\mathrm{F}\). One possible selection of two people is \(\mathrm{A}\) and \(\mathrm{B}\). There are 14 other possible selections to consider.) b. Are the outcomes in the sample space equally likely? c. What is the probability that both the chosen contestants are younger than \(25 ?\) d. What is the probability that both the chosen contestants are not younger than \(25 ?\) e. What is the probability that one is younger than 25 and the other is not?

Short Answer

Expert verified
a. The sample space consists of 15 possible pairs: {AB, AC, AD, AE, AF, BC, BD, BE, BF, CD, CE, CF, DE, DF, EF} b. Yes, the outcomes in the sample space are equally likely, with each pair having a probability of \(\frac{1}{15}\) c. The probability that both the chosen contestants are younger than 25 is \(\frac{1}{15}\) d. The probability that both the chosen contestants are not younger than 25 is \(\frac{6}{15}\) e. The probability that one is younger than 25 and the other is not is \(\frac{8}{15}\)

Step by step solution

01

Identify the possible combinations

First, we will find the sample space, i.e., the number of possible ways to select two contestants from the six people. Let's label the people as A, B, C, D, E, and F, where A, B are the ones younger than 25 years old. Use combinations to find the possible ways: \[\binom{6}{2} = \frac{6!}{(2!(6-2)!)} = \frac{6 \times 5}{2} = 15\] hence, there are 15 possible ways to select two contestants.
02

Enumerate the Sample Space

Now let's find the actual selections (pairs) possible: {AB, AC, AD, AE, AF, BC, BD, BE, BF, CD, CE, CF, DE, DF, EF}
03

Assess the Equally Likely Outcomes

As every person has the same chance of being selected, the sample space outcomes are equally likely. Each pair has a probability of \(\frac{1}{15}\) of being chosen.
04

Calculate the Probability of Both Contestants Being Younger Than 25

Since A and B are the contestants who are younger than 25, there is only 1 out of the 15 possible pairs that have both contestants younger than 25. So, the probability will be: \[\frac{1}{15}\]
05

Calculate the Probability of Both Contestants NOT Being Younger Than 25

There are four people older than 25, and we need to find the pairs with those people only. Use combinations here as well. \[\binom{4}{2} = \frac{4!}{(2!(4-2)!)} = \frac{4 \times 3}{2} = 6\] So, there are 6 possible pairs of contestants older than 25, and hence, the probability of both contestants being not younger than 25 is: \[\frac{6}{15}\]
06

Calculate the Probability of One Contestant Being Younger Than 25 and the Other Being Not Younger Than 25

This case can be seen as complementary to the other two cases, so the probability can be calculated using the complementary rule: \[P(\text{one younger, one not}) = 1 - P(\text{both younger}) - P(\text{both older})\] \[P(\text{one younger, one not}) = 1 - \frac{1}{15} - \frac{6}{15}\] \[P(\text{one younger, one not}) = \frac{8}{15} \]

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Combinatorics
Combinatorics is a branch of mathematics that deals with counting, arranging, and ordering objects. In our exercise, we use combinatorics to determine how many ways we can select two contestants from a group of six people. The formula we use is the combination formula, which is given by \( \binom{n}{r} = \frac{n!}{r!(n-r)!} \). Here, \( n \) signifies the total number of items (or people, in this case), and \( r \) is the number of items to choose.
We applied this formula to find \( \binom{6}{2} = 15 \), indicating that there are 15 possible combinations of choosing two people from six. This foundational step is crucial as it lays down the sample space for further probability calculations.
Sample Space
In probability theory, the sample space represents the set of all possible outcomes of a probability experiment. In the exercise at hand, the sample space involves combinations of selecting two people from a group of six.
By labeling the people as A, B, C, D, E, and F, and employing the concept of combinations, we derive the complete sample space as: {AB, AC, AD, AE, AF, BC, BD, BE, BF, CD, CE, CF, DE, DF, EF}.
  • *Sample Space*: Collection of all possible pairs {AB, AC, AD, AE, AF, BC, BD, BE, BF, CD, CE, CF, DE, DF, EF}
  • Size of Sample Space = 15 pairs, reflecting all possible contestant selections.
With the sample space defined, we can move forward to determining probabilities of finding specific arrangements within these 15 combinations.
Equally Likely Outcomes
When discussing probability, an equally likely outcome means each event in the sample space has the same chance of occurring. For example, in the TV game show contestant selection, each pair of two people has the same chance of being picked.
Since we're randomly selecting the contestants without bias, each outcome in our 15-member sample space has a probability of \( \frac{1}{15} \).
  • This reflects the unbiased nature of random selection.
  • Ensures fairness in the selection process, as every possible pair stands the same chance.
Understanding this concept helps in accurately calculating the probabilities of specific events occurring in our problem.
Complementary Rule
The complementary rule in probability is a powerful tool that simplifies calculating the probability of specific events. It involves understanding that the probability of an event not happening is 1 minus the probability of it happening.
In our exercise, we calculate the probability that one contestant is younger than 25 and the other is not using this rule. Since we know the probabilities for both being younger and both being not younger, the complementary probability is:
  • \[P(\text{one younger, one not}) = 1 - P(\text{both younger}) - P(\text{both older})\]
  • Calculated as \( \frac{8}{15} \), ensuring we cover all other possible combinations.
The complementary rule is valuable as it helps derive probabilities efficiently and accurately, especially when multiple situations blend into one exhaustive probability division.

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Most popular questions from this chapter

Are people more confident in their answers when the answer is actually correct than when it is not? The article "Female Students Less Confident, More Accurate Than Male Counterparts" described a study that measured medical students" confidence and the accuracy of their responses. Participants categorized their confidence levels using either "sure," "feeling lucky," or "no clue" Define the following events: \(C=\) event that a response is conect \(S=\) event that confidence level is "sure" \(L=\) event that confidence level is "feeling lucky" \(N=\) event that confidence level is "no clue" a. Data from the article were used to estimate the following probabilities for males: $$ \begin{array}{rrr} P(S)=0.442 & P(L)=0.422 & P(N)=0.136 \\ P(C \mid S)=0.783 & P(C \mid L)=0.498 & P(C \mid N)=0.320 \end{array} $$ Use the given probabilities to construct a hypothetical 1000 table with rows corresponding to confidence level and columns comesponding to whether the response was correct or not. b. Calculate the probability that a male student's confidence level is "sure" given that the response is correct. c. Calculate the probability that a male student's confidence level is "no clue" given that the response is incorrect. d. Calculate the probability that a male student's response is correct. e. Data from the article were also used to estimate the following probabilities for females: $$ \begin{array}{rrr} P(S)=0.395 & P(L)=0.444 & P(N)=0.161 \\ P(C 1 S)=0.805 & P(C \mid L)=0.535 & P(C \mid N)=0.320 \end{array} $$ Use the given probabilities to construct a hypothetical 1000 table with rows corresponding to confidence level and columns corresponding to whether the response was comect or not. f. Calculate the probability that a female student's confidence level is "sure" given that the response is correct. g. Calculate the probability that a female student's confidence level is "no clue" given that the response is incorrect. h. Calculate the probability that a female student's response is correct. i. Do the given probabilities and the probabilities that you calculated support the statement in the title of the article? Explain.

Consider a chance experiment that consists of selecting a customer at random from all people who purchased a car at a large car dealership during 2016 . a. In the context of this chance experiment, give an example of two events that would be mutually exclusive. b. In the context of this chance experiment, give an example of two events that would not be mutually exclusive.

A large cable company reports that \(80 \%\) of its customers subscribe to its cable TV service, \(42 \%\) subscribe to its Internet service, and \(97 \%\) subscribe to at least one of these two services. a. Use the given probability information to set up a hypothetical 1000 table. b. Use the table from Part (a) to find the following probabilities: i. the probability that a randomly selected customer subscribes to both cable TV and Internet service. ii. the probability that a randomly selected customer subscribes to exactly one of these services.

Airline tickets can be purchased online, by telephone, or by using a travel agent. Passengers who have a ticket sometimes don't show up for their flights. Suppose a person who purchased a ticket is selected at random. Consider the following events: \(O=\) event selected person purchased ticket online \(N=\) event selected person did not show up for flight Suppose \(P(O)=0.70, P(N)=0.07,\) and \(P(O \cap N)=0.04\) a. Are the events \(N\) and \(O\) independent? How can you tell? b. Construct a hypothetical 1000 table with columns corresponding to \(N\) and \(\operatorname{not} N\) and rows corresponding to \(O\) and \(\operatorname{not} O\). c. Use the table to find \(P(O \cup N)\). Give a relative frequency interpretation of this probability.

In a particular state, automobiles that are more than 10 years old must pass a vehicle inspection in order to be registered. This state reports the probability that a car more than 10 years old will fail the vehicle inspection is 0.09 . Give a relative frequency interpretation of this probability.

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