Here are summary statistics for randomly selected weights of newborn girls: n = 206, x= 33.6 hg, s= 7.8 hg. Construct a confidence interval estimate of the mean. Use a 98% confidence level. Are these results very different from the confidence interval 31.6 hg

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**Constructing a Confidence Interval**

Assume that we want to construct a confidence interval. Do one of the following, as appropriate: (a) find the critical value \( t_{\alpha/2} \), (b) find the critical value \( z_{\alpha/2} \), or (c) state that neither the normal distribution nor the t distribution applies.

The confidence level is 90%, \( \sigma \) is not known, and the histogram of 61 player salaries (in thousands of dollars) of football players on a team is as shown.

**Histogram Explanation:**

- **X-axis (Salary - thousands of dollars):** Ranges from 0 to 2000.
- **Y-axis (Frequency):** Ranges from 0 to 40.
- The distribution is right-skewed, with the highest frequency (around 38) at the 0 to 4000 interval.

**Choices:**

Select the correct choice below and, if necessary, fill in the answer box to complete your choice.

- A. \( t_{\alpha/2} = \) [____]  
  (Round to two decimal places as needed.)

- B. \( z_{\alpha/2} = \) [____]  
  (Round to two decimal places as needed.)

- C. Neither the normal distribution nor the t distribution applies.
Transcribed Image Text:**Constructing a Confidence Interval** Assume that we want to construct a confidence interval. Do one of the following, as appropriate: (a) find the critical value \( t_{\alpha/2} \), (b) find the critical value \( z_{\alpha/2} \), or (c) state that neither the normal distribution nor the t distribution applies. The confidence level is 90%, \( \sigma \) is not known, and the histogram of 61 player salaries (in thousands of dollars) of football players on a team is as shown. **Histogram Explanation:** - **X-axis (Salary - thousands of dollars):** Ranges from 0 to 2000. - **Y-axis (Frequency):** Ranges from 0 to 40. - The distribution is right-skewed, with the highest frequency (around 38) at the 0 to 4000 interval. **Choices:** Select the correct choice below and, if necessary, fill in the answer box to complete your choice. - A. \( t_{\alpha/2} = \) [____] (Round to two decimal places as needed.) - B. \( z_{\alpha/2} = \) [____] (Round to two decimal places as needed.) - C. Neither the normal distribution nor the t distribution applies.
Here are summary statistics for randomly selected weights of newborn girls: n = 206, \(\bar{x} = 33.6\) hg, \(s = 7.8\) hg. Construct a confidence interval estimate of the mean. Use a 98% confidence level. Are these results very different from the confidence interval 31.6 hg < \(\mu\) < 35.8 hg with only 17 sample values, \(\bar{x} = 33.7\) hg, and \(s = 3.4\) hg?

What is the confidence interval for the population mean \(\mu\)?

\[
\text{▢ hg} < \mu < \text{▢ hg} \quad (\text{Round to one decimal place as needed.})
\]

Are the results between the two confidence intervals very different?

- A. No, because the confidence interval limits are similar.
- B. No, because each confidence interval contains the mean of the other confidence interval.
- C. Yes, because one confidence interval does not contain the mean of the other confidence interval.
- D. Yes, because the confidence interval limits are not similar.
Transcribed Image Text:Here are summary statistics for randomly selected weights of newborn girls: n = 206, \(\bar{x} = 33.6\) hg, \(s = 7.8\) hg. Construct a confidence interval estimate of the mean. Use a 98% confidence level. Are these results very different from the confidence interval 31.6 hg < \(\mu\) < 35.8 hg with only 17 sample values, \(\bar{x} = 33.7\) hg, and \(s = 3.4\) hg? What is the confidence interval for the population mean \(\mu\)? \[ \text{▢ hg} < \mu < \text{▢ hg} \quad (\text{Round to one decimal place as needed.}) \] Are the results between the two confidence intervals very different? - A. No, because the confidence interval limits are similar. - B. No, because each confidence interval contains the mean of the other confidence interval. - C. Yes, because one confidence interval does not contain the mean of the other confidence interval. - D. Yes, because the confidence interval limits are not similar.
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