Concept explainers
Unsanitary Restaurants
Health officials routinely check the sanitary condition of restaurants. Assume you visit a popular tourist spot and read in the newspaper that in 3 out of every 7 restaurants checked, unsatisfactory health conditions were found. Assuming you are planning to eat out 10 times while you are there on vacation, answer the following questions.
1. How likely is it that you will eat at three restaurants with unsanitary conditions?
2. How likely is it that you will eat at four or five restaurants with unsanitary conditions?
3. Explain how you would compute the
4. What is the most likely number to occur in this experiment?
5. How variable will the data be around the most likely number?
6. How do you know that this is a binomial distribution?
7. If it is a binomial distribution, does that
Mean = 4.29 Std. dev. = 1.56492
X | P(X) | Cum. prob. |
0 | 0.00371 | 0.00371 |
1 | 0.02784 | 0.03155 |
2 | 0.09396 | 0.12552 |
3 | 0.18793 | 0.31344 |
4 | 0.24665 | 0.56009 |
5 | 0.22199 | 0.78208 |
6 | 0.13874 | 0.92082 |
7 | 0.05946 | 0.98028 |
8 | 0.01672 | 0.99700 |
9 | 0.00279 | 0.99979 |
10 | 0.00021 | 1.00000 |
a.
The probability that the person is likely to eat at all three restaurants with unsanitary conditions.
Answer to Problem 1AC
The probability the person is likely to eat at all three restaurants with unsanitary conditions is 0.186.
Explanation of Solution
Given info:
A person is planning to eat outside 10 times during a vacation. Health officials checks the sanitary condition of restaurant and found that every 3 out of 7 restaurants checked was having an unsatisfactory health conditions.
Calculation:
Define the random variable x as the number of restaurants with unsanitary conditions. Here, the total number of restaurants are (n) is 10 and each restaurant is independent from other restaurants. Also, there are two possible outcomes (having an unsanitary conditions or didn’t have an unsanitary conditions) and the probability of that the selected restaurant having an unsanitary conditions gives the probability (p)
The binomial distribution formula is,
Where, n is the number of trials, x is the number of successes among n trials, p is the probability of success and q is the probability of failure.
Substitute n as 10, p as 0.43, q as
Thus, the probability the person is likely to eat at all three restaurants with unsanitary conditions is 0.186.
b.
The probability that the person is likely to eat at four or five restaurants with unsanitary conditions.
Answer to Problem 1AC
The probability the person is likely to eat at four or five restaurants with unsanitary conditions is 0.469.
Explanation of Solution
Here, “Eating at four or five restaurants with unsanitary conditions gives the values of X as 4 and 5.
Substitute n as 10, p as 0.43, q as
Thus, the probability the person is likely to eat at four or five restaurants with unsanitary conditions is 0.469.
c.
To explain: The way to compute the probability of eating in at least one restaurant with unsanitary conditions.
To find: The probability of eating in at least one restaurant with unsanitary conditions.
Answer to Problem 1AC
The way to compute the probability of eating in at least one restaurant with unsanitary conditions is given below:
Eating in at least one restaurant is same as eating in 1 or more than 1 restaurants.
The probability of eating in at least one restaurant with unsanitary conditions is 0.9964.
Explanation of Solution
Calculation:
Substitute n as 10, p as 0.43, q as
=0.9964
Thus, the probability of eating in at least one restaurant is 0.9964.
d.
The most likely number that could occur in the given experiment.
Answer to Problem 1AC
The most likely number that could occur in the given experiment is the event of eating in 4 restaurants with unsanitary conditions.
Explanation of Solution
Calculation:
Software procedure:
Software procedure for calculating the probability is given below:
- Choose Calc > Probability Distributions > Binomial Distribution.
- Choose Probability.
- Enter Number of trials as 10 and Event probability as 0.43.
- In Input columns, enter the column containing the values 0, 1, 2, 3,…10.
- Click OK.
Output obtained from MINITAB is given below:
Justification:
From the MINITAB output it can be observed that the probability of eating in 4 restaurants has the highest probability of 0.2462.
The probability for 4 restaurants is the highest, but the expected number of restaurants that a person would eat is
e.
To find: The variability of the data around the most likely number.
Answer to Problem 1AC
The variability of the data around the most likely number would be 1.565 restaurants.
Explanation of Solution
Calculation:
Standard deviation:
Substitute n as 10, p as 0.43 and q as
Thus, the variability of the data around the most likely number would be 1.565 restaurants.
f.
To justify: The reason for identifying the given experiment as binomial.
Answer to Problem 1AC
The given experiment satisfies all the “requirements of binomial distribution”.
Explanation of Solution
Justification:
Requirements of binomial distribution:
- There will be a fixed number of trials.
- There are only two possible outcomes (success and failure).
- The probability of success remains constant.
- The outcomes obtained from each trial are independent of one another.
Here, the number of restaurants is 10 and it gives the fixed number of trials, there are only two possible outcomes either a restaurant might have unsanitary condition or a restaurant might not have unsanitary condition. The probability of that the selected restaurant having an unsanitary conditions gives the probability (p)
Thus, the given experiment is a binomial distribution.
g.
To check: Whether the mean of the likelihood of success is always 50%.
Answer to Problem 1AC
The mean of the likelihood of success will vary from situation to situation.
Explanation of Solution
Given info:
Use the computer generated table for checking.
Justification:
In binomial distribution the probability of success remains constant and it is 50% but it varies for situation to situation. Just having two outcomes will not assurance for equal probabilities of success.
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