i) Test the claim of u> 2015 and use c=.90. Provide a sketch of the Critical Value. Evaluate the Test Statistic and provide the p-value. Only for this part use o = 23.8

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### Statistical Hypothesis Testing

**Problem Statement:**

i) Test the claim of \( \mu > 2015 \) and use \( \alpha = 0.10 \). Provide a sketch of the Critical Value. Evaluate the Test Statistic and provide the p-value. Only for this part, use \( \sigma = 23.8 \).

**Solution Guide:**

1. **Set up the Hypothesis:**
   - Null Hypothesis (\( H_0 \)): \( \mu \leq 2015 \)
   - Alternative Hypothesis (\( H_a \)): \( \mu > 2015 \)

2. **Determine the Critical Value:**
   - Since the test is right-tailed, use a significance level (\( \alpha \)) of 0.10.
   - Find the critical value from the standard normal distribution table corresponding to \( \alpha = 0.10 \).

3. **Calculate the Test Statistic:**
   - Use the formula for the z-test statistic:
     \[
     z = \frac{\bar{x} - \mu}{\sigma/\sqrt{n}}
     \]
   - Plug in the known values to find the z-value.

4. **P-Value and Decision:**
   - Use the standard normal distribution to find the p-value.
   - Compare the p-value to the significance level (\( \alpha \)).

5. **Sketch of Critical Value:**
   - Diagram illustrating the normal distribution curve.
   - Highlight the critical region on the far right-hand side representing 10% of the area under the curve.

**Conclusion:**
Based on the calculated test statistic and p-value, determine if there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis.

**Note:** Detailed steps with numerical calculations should be carried out with specific data values if provided.
Transcribed Image Text:### Statistical Hypothesis Testing **Problem Statement:** i) Test the claim of \( \mu > 2015 \) and use \( \alpha = 0.10 \). Provide a sketch of the Critical Value. Evaluate the Test Statistic and provide the p-value. Only for this part, use \( \sigma = 23.8 \). **Solution Guide:** 1. **Set up the Hypothesis:** - Null Hypothesis (\( H_0 \)): \( \mu \leq 2015 \) - Alternative Hypothesis (\( H_a \)): \( \mu > 2015 \) 2. **Determine the Critical Value:** - Since the test is right-tailed, use a significance level (\( \alpha \)) of 0.10. - Find the critical value from the standard normal distribution table corresponding to \( \alpha = 0.10 \). 3. **Calculate the Test Statistic:** - Use the formula for the z-test statistic: \[ z = \frac{\bar{x} - \mu}{\sigma/\sqrt{n}} \] - Plug in the known values to find the z-value. 4. **P-Value and Decision:** - Use the standard normal distribution to find the p-value. - Compare the p-value to the significance level (\( \alpha \)). 5. **Sketch of Critical Value:** - Diagram illustrating the normal distribution curve. - Highlight the critical region on the far right-hand side representing 10% of the area under the curve. **Conclusion:** Based on the calculated test statistic and p-value, determine if there is enough evidence to reject the null hypothesis in favor of the alternative hypothesis. **Note:** Detailed steps with numerical calculations should be carried out with specific data values if provided.
Use the following data set: 40, 33, 77, 12, 23, 56, 23, 19, 29 (minutes). Assume the data is approximately bell-shaped and a sample.
Transcribed Image Text:Use the following data set: 40, 33, 77, 12, 23, 56, 23, 19, 29 (minutes). Assume the data is approximately bell-shaped and a sample.
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