About 10% of babies born with a certain ailment recover fully. A hospital is caring for seven babies born with this ailment. The random variable represents the number of babies that recover fully. Decide whether the experiment is a binomial experiment. If it is, identify a success, specify the values of n, p, and q, and list the possible values of the random variable x. Is the experiment binomial experiment? O No Yes What is a success in this experiment? Baby doesn't recover O This is not a binomial experiment. Baby recovers Specify the value of n. Select the correct choice below and fill in any answer boxes in your choice. OA. n= OB. This is not a binomial experiment. C

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## Binomial Experiment Analysis in Medical Recovery Rates

### Overview
About 10% of babies born with a certain ailment recover fully. A hospital is caring for seven babies born with this ailment. The random variable represents the number of babies that recover fully. We will determine whether this scenario qualifies as a binomial experiment, identify a success, specify the values of \( n \), \( p \), and \( q \), and list the possible values of the random variable \( x \).

### Determining if the Experiment is Binomial
**Is the experiment a binomial experiment?**

- [ ] No
- [x] Yes

### Identifying a Success
**What is a success in this experiment?**

- [x] Baby recovers
- [ ] Baby doesn't recover
- [ ] This is not a binomial experiment.

### Specifying \( n \)
**Specify the value of \( n \). Select the correct choice below and fill in any answer boxes in your choice.**

- [ ] This is not a binomial experiment.
- [x] \( n = \_ \)

   Answer: \( n = 7 \)

### Explanation
- **Random Variable (\( x \)):** The number of babies that recover fully.
- **Total Number of Trials (\( n \)):** The number of babies being observed (7 babies).
- **Probability of Success in a Single Trial (\( p \)):** The probability that one baby recovers fully (0.1 or 10%).
- **Probability of Failure in a Single Trial (\( q \)):** The probability that one baby does not recover fully ( \( q = 1 - p \), thus \( q = 0.9 \)).

By specifying the value of \( n = 7 \), we confirm that this is a binomial experiment as the conditions of fixed number of trials, only two possible outcomes (success or failure), independence of trials, and constant probability of success are met.
Transcribed Image Text:## Binomial Experiment Analysis in Medical Recovery Rates ### Overview About 10% of babies born with a certain ailment recover fully. A hospital is caring for seven babies born with this ailment. The random variable represents the number of babies that recover fully. We will determine whether this scenario qualifies as a binomial experiment, identify a success, specify the values of \( n \), \( p \), and \( q \), and list the possible values of the random variable \( x \). ### Determining if the Experiment is Binomial **Is the experiment a binomial experiment?** - [ ] No - [x] Yes ### Identifying a Success **What is a success in this experiment?** - [x] Baby recovers - [ ] Baby doesn't recover - [ ] This is not a binomial experiment. ### Specifying \( n \) **Specify the value of \( n \). Select the correct choice below and fill in any answer boxes in your choice.** - [ ] This is not a binomial experiment. - [x] \( n = \_ \) Answer: \( n = 7 \) ### Explanation - **Random Variable (\( x \)):** The number of babies that recover fully. - **Total Number of Trials (\( n \)):** The number of babies being observed (7 babies). - **Probability of Success in a Single Trial (\( p \)):** The probability that one baby recovers fully (0.1 or 10%). - **Probability of Failure in a Single Trial (\( q \)):** The probability that one baby does not recover fully ( \( q = 1 - p \), thus \( q = 0.9 \)). By specifying the value of \( n = 7 \), we confirm that this is a binomial experiment as the conditions of fixed number of trials, only two possible outcomes (success or failure), independence of trials, and constant probability of success are met.
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