Determining the Critical Value A random sample of 240 doctors revealed that 108 are satisfied with the current state of US health care. 108(1 - 108) 108 ±1.645, 240 The conditions for inference are met. Using z* = 1.645, which expression gives a 90% confidence interval for the true proportion of all US 0.5(1-0.5) 1.645 +108, 240 doctors who are satisfied with the current state of US health care? 0.45 (1-0.45) 0.45 ±1.645, 240 0.5(1- 0.5) 0.45 ±108, 1.645

MATLAB: An Introduction with Applications
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Chapter1: Starting With Matlab
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A random sample of 240 doctors revealed that 108 are satisfied with the current state of US health care.

The conditions for inference are met.

Using z* = 1.645, which expression gives a 90% confidence interval for the true proportion of all US doctors who are satisfied with the current state of US health care?

**Determining the Critical Value**

A random sample of 240 doctors revealed that 108 are satisfied with the current state of US health care.

The conditions for inference are met.

Using \( z^* = 1.645 \), which expression gives a 90% confidence interval for the true proportion of all US doctors who are satisfied with the current state of US health care?

1. \( 108 \pm 1.645 \sqrt{\frac{108(1-108)}{240}} \)

2. \( 1.645 \pm 108 \sqrt{\frac{0.5(1-0.5)}{240}} \)

3. \( 0.45 \pm 1.645 \sqrt{\frac{0.45(1-0.45)}{240}} \)

4. \( 0.45 \pm 108 \sqrt{\frac{0.5(1-0.5)}{1.645}} \)

**Explanation:**

- The task is to find the correct expression for calculating a 90% confidence interval.
- \( z^* = 1.645 \) is the critical value for a 90% confidence level.
- The sample proportion is calculated as \( \frac{108}{240} = 0.45 \).
- The expression should use this sample proportion in its calculation with the formula:

  \[
  \text{Sample Proportion} \pm z^* \sqrt{\frac{\text{Sample Proportion}(1-\text{Sample Proportion})}{\text{Sample Size}}}
  \]

The correct expression that fits this format is:

- \( 0.45 \pm 1.645 \sqrt{\frac{0.45(1-0.45)}{240}} \)

This choice correctly uses the sample proportion of 0.45 and incorporates the critical value \( z^* \) correctly in the confidence interval formula.
Transcribed Image Text:**Determining the Critical Value** A random sample of 240 doctors revealed that 108 are satisfied with the current state of US health care. The conditions for inference are met. Using \( z^* = 1.645 \), which expression gives a 90% confidence interval for the true proportion of all US doctors who are satisfied with the current state of US health care? 1. \( 108 \pm 1.645 \sqrt{\frac{108(1-108)}{240}} \) 2. \( 1.645 \pm 108 \sqrt{\frac{0.5(1-0.5)}{240}} \) 3. \( 0.45 \pm 1.645 \sqrt{\frac{0.45(1-0.45)}{240}} \) 4. \( 0.45 \pm 108 \sqrt{\frac{0.5(1-0.5)}{1.645}} \) **Explanation:** - The task is to find the correct expression for calculating a 90% confidence interval. - \( z^* = 1.645 \) is the critical value for a 90% confidence level. - The sample proportion is calculated as \( \frac{108}{240} = 0.45 \). - The expression should use this sample proportion in its calculation with the formula: \[ \text{Sample Proportion} \pm z^* \sqrt{\frac{\text{Sample Proportion}(1-\text{Sample Proportion})}{\text{Sample Size}}} \] The correct expression that fits this format is: - \( 0.45 \pm 1.645 \sqrt{\frac{0.45(1-0.45)}{240}} \) This choice correctly uses the sample proportion of 0.45 and incorporates the critical value \( z^* \) correctly in the confidence interval formula.
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