Olivia, Nicholas, Chloe, and Ethan each took many samples from the same population of students. The number of students in each of their samples is shown in the table below. Which person's sampling distribution is most likely to closely approximate the population distribution?

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### Sampling Distribution Comparison

Olivia, Nicholas, Chloe, and Ethan each took many samples from the same population of students. The number of students in each of their samples is shown in the table below. Which person's sampling distribution is most likely to closely approximate the population distribution?

| **Person taking sample** | **Number of students in each sample** |
|----------------------------|--------------------------------------|
| Olivia                     | 29                                   |
| Nicholas                   | 91                                   |
| Chloe                      | 56                                   |
| Ethan                      | 70                                   |

In this example, each individual (Olivia, Nicholas, Chloe, and Ethan) collected different-sized samples from a student population. To determine whose sampling distribution most closely approximates the population distribution, it's essential to consider the number of students in each sample. Generally, larger samples tend to provide better approximations of the population distribution due to their higher likelihood of capturing the population's characteristics.

- **Olivia** collected a sample of 29 students.
- **Nicholas** collected a sample of 91 students.
- **Chloe** collected a sample of 56 students.
- **Ethan** collected a sample of 70 students.

Based on the number of students in each sample, **Nicholas**, with the largest sample size of 91 students, is most likely to have a sampling distribution that closely approximates the population distribution.
Transcribed Image Text:### Sampling Distribution Comparison Olivia, Nicholas, Chloe, and Ethan each took many samples from the same population of students. The number of students in each of their samples is shown in the table below. Which person's sampling distribution is most likely to closely approximate the population distribution? | **Person taking sample** | **Number of students in each sample** | |----------------------------|--------------------------------------| | Olivia | 29 | | Nicholas | 91 | | Chloe | 56 | | Ethan | 70 | In this example, each individual (Olivia, Nicholas, Chloe, and Ethan) collected different-sized samples from a student population. To determine whose sampling distribution most closely approximates the population distribution, it's essential to consider the number of students in each sample. Generally, larger samples tend to provide better approximations of the population distribution due to their higher likelihood of capturing the population's characteristics. - **Olivia** collected a sample of 29 students. - **Nicholas** collected a sample of 91 students. - **Chloe** collected a sample of 56 students. - **Ethan** collected a sample of 70 students. Based on the number of students in each sample, **Nicholas**, with the largest sample size of 91 students, is most likely to have a sampling distribution that closely approximates the population distribution.
### Multiple Choice Question:

Please select your answer from the options below:

- **A. Olivia**

- **B. Nicholas**

- **C. Ethan**

- **D. Chloe**

(Note: This image appears to be part of an online quiz or survey where participants are required to choose one of the options provided.)
Transcribed Image Text:### Multiple Choice Question: Please select your answer from the options below: - **A. Olivia** - **B. Nicholas** - **C. Ethan** - **D. Chloe** (Note: This image appears to be part of an online quiz or survey where participants are required to choose one of the options provided.)
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