Suppose the mean number of people attending all 2017 Veterans Day celebrations held in Virginia is 182 with a standard deviation of 37 people. A few of the celebrations are huge, and hence the distribution is skewed heavily to the right. If a simple random sample of 54 Veterans Day celebrations held in Virginia is selected and the number of people in attendance determined for each, describe completely the sampling distribution of, the resulting mean number of people attending for this sample of 54 Veterans Day celebrations held in Virginia. 3.335 24 What is the spread of the sampling distribution? 156 134 5.035 4.318 182 3.335 25 000 What is the shape of the sampling distribution? Bimodal Normal Slightly Skewed Left Heavily Skewed Right Slightly Skewed Right

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### Sampling Distribution Analysis: Veterans Day Celebrations in Virginia

**Background Context:**

The average number of people attending Veterans Day celebrations in Virginia in 2017 is reported to be 182, with a corresponding standard deviation of 37 individuals. Due to a few large celebrations, the data distribution is significantly right-skewed.

**Scenario for Analysis:**

Consider a random sample consisting of 54 Veterans Day celebrations. We aim to determine the sampling distribution of the mean number of attendees calculated from this sample. Below is a comprehension of the sampling distribution's spread and shape based on this scenario.

**Question 24: Spread of the Sampling Distribution**

"What is the spread of the sampling distribution?"

- 156
- 134
- 5.035
- 4.318
- 182
- 3.335

**Answer Considerations:**

The spread (standard error) of the sampling distribution of the sample mean is calculated with the formula: 

\[ \text{Standard Error (SE)} = \frac{\sigma}{\sqrt{n}} \]

where:
- \(\sigma\) is the population standard deviation (37),
- \(n\) is the sample size (54).

\[ \text{SE} = \frac{37}{\sqrt{54}} ≈ 5.035 \]

Hence, the correct answer is **5.035**.

**Question 25: Shape of the Sampling Distribution**

"What is the shape of the sampling distribution?"

- Bimodal
- Normal
- Slightly Skewed Left
- Heavily Skewed Right
- Slightly Skewed Right

**Answer Considerations:**

Given the Central Limit Theorem, for sufficiently large sample sizes, the sampling distribution of the sample mean will approximate a normal distribution, regardless of the population's distribution shape. Here, with a sample size of 54, the shape of the sampling distribution can be approximated to be **Normal**.

### Visual Aids

*Currently, no diagrams or visual graphs accompany the text. If applicable, consider adding characteristic diagrams demonstrating the skewness of distributions and the transformational effect of large sample sizes towards normality in sampling distributions.*

---

This analysis aids understanding of key concepts in statistical sampling and distribution for educational purposes.
Transcribed Image Text:### Sampling Distribution Analysis: Veterans Day Celebrations in Virginia **Background Context:** The average number of people attending Veterans Day celebrations in Virginia in 2017 is reported to be 182, with a corresponding standard deviation of 37 individuals. Due to a few large celebrations, the data distribution is significantly right-skewed. **Scenario for Analysis:** Consider a random sample consisting of 54 Veterans Day celebrations. We aim to determine the sampling distribution of the mean number of attendees calculated from this sample. Below is a comprehension of the sampling distribution's spread and shape based on this scenario. **Question 24: Spread of the Sampling Distribution** "What is the spread of the sampling distribution?" - 156 - 134 - 5.035 - 4.318 - 182 - 3.335 **Answer Considerations:** The spread (standard error) of the sampling distribution of the sample mean is calculated with the formula: \[ \text{Standard Error (SE)} = \frac{\sigma}{\sqrt{n}} \] where: - \(\sigma\) is the population standard deviation (37), - \(n\) is the sample size (54). \[ \text{SE} = \frac{37}{\sqrt{54}} ≈ 5.035 \] Hence, the correct answer is **5.035**. **Question 25: Shape of the Sampling Distribution** "What is the shape of the sampling distribution?" - Bimodal - Normal - Slightly Skewed Left - Heavily Skewed Right - Slightly Skewed Right **Answer Considerations:** Given the Central Limit Theorem, for sufficiently large sample sizes, the sampling distribution of the sample mean will approximate a normal distribution, regardless of the population's distribution shape. Here, with a sample size of 54, the shape of the sampling distribution can be approximated to be **Normal**. ### Visual Aids *Currently, no diagrams or visual graphs accompany the text. If applicable, consider adding characteristic diagrams demonstrating the skewness of distributions and the transformational effect of large sample sizes towards normality in sampling distributions.* --- This analysis aids understanding of key concepts in statistical sampling and distribution for educational purposes.
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