The National Weather Service says that the mean daily high temperature for October in a large Midwestern city is 57°F. A local weather service suspects that this value is not accurate and wants to perform a hypothesis test to determine whether the mean is actually lower than 57°FA sample of mean daily high temperatures for October over past 30 years yields X = 55° F Assume that the population standard deviation is 5.7°F. Perform the hypothesis test at the a = 0.01 significance level. %3D

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### Hypothesis Testing on Mean Daily High Temperature

The National Weather Service states that the mean daily high temperature for October in a large Midwestern city is \( 57^\circ F \). A local weather service suspects that this value is not accurate and wants to perform a hypothesis test to determine whether the mean is actually lower than \( 57^\circ F \). 

### Given Data
- Sample Mean (\(\bar{X}\)): \( 55^\circ F \)
- Population Standard Deviation (\(\sigma\)): \( 5.7^\circ F \)
- Significance Level (\(\alpha\)): 0.01

We want to perform the hypothesis test at the \(\alpha = 0.01\) significance level.

### Hypothesis Statements

1. Greater than \(57^\circ F\):
   - Null Hypothesis (\(H_0\)): \( \mu = 57^\circ F \)
   - Alternative Hypothesis (\(H_a\)): \( \mu > 57^\circ F \)
   - Test statistics: \( z = -1.92 \)
   - Critical Value: \( z = -2.33 \)

   - Conclusion: Fail to reject \(H_0: \mu = 57^\circ F\). There is not sufficient evidence to support the claim that the mean is greater than \(57^\circ F\).

2. Less than \(57^\circ F\):
   - Null Hypothesis (\(H_0\)): \( \mu = 57^\circ F \)
   - Alternative Hypothesis (\(H_a\)): \( \mu < 57^\circ F \)
   - Test statistics: \( z = -1.92 \)
   - Critical Value: \( z = -2.33 \)

   - Conclusion: Fail to reject \(H_0: \mu = 57^\circ F\). There is not sufficient evidence to support the claim that the mean is less than \(57^\circ F\).

### Summary
For both hypothesis tests, the test statistics provided (\(z = -1.92\)) is compared against the critical value (\(z = -2.33\)). In both cases, the null hypothesis is not rejected, indicating insufficient evidence to support either of the alternative hypotheses regarding the mean daily high temperatures differing from \( 57^\circ F \).
Transcribed Image Text:### Hypothesis Testing on Mean Daily High Temperature The National Weather Service states that the mean daily high temperature for October in a large Midwestern city is \( 57^\circ F \). A local weather service suspects that this value is not accurate and wants to perform a hypothesis test to determine whether the mean is actually lower than \( 57^\circ F \). ### Given Data - Sample Mean (\(\bar{X}\)): \( 55^\circ F \) - Population Standard Deviation (\(\sigma\)): \( 5.7^\circ F \) - Significance Level (\(\alpha\)): 0.01 We want to perform the hypothesis test at the \(\alpha = 0.01\) significance level. ### Hypothesis Statements 1. Greater than \(57^\circ F\): - Null Hypothesis (\(H_0\)): \( \mu = 57^\circ F \) - Alternative Hypothesis (\(H_a\)): \( \mu > 57^\circ F \) - Test statistics: \( z = -1.92 \) - Critical Value: \( z = -2.33 \) - Conclusion: Fail to reject \(H_0: \mu = 57^\circ F\). There is not sufficient evidence to support the claim that the mean is greater than \(57^\circ F\). 2. Less than \(57^\circ F\): - Null Hypothesis (\(H_0\)): \( \mu = 57^\circ F \) - Alternative Hypothesis (\(H_a\)): \( \mu < 57^\circ F \) - Test statistics: \( z = -1.92 \) - Critical Value: \( z = -2.33 \) - Conclusion: Fail to reject \(H_0: \mu = 57^\circ F\). There is not sufficient evidence to support the claim that the mean is less than \(57^\circ F\). ### Summary For both hypothesis tests, the test statistics provided (\(z = -1.92\)) is compared against the critical value (\(z = -2.33\)). In both cases, the null hypothesis is not rejected, indicating insufficient evidence to support either of the alternative hypotheses regarding the mean daily high temperatures differing from \( 57^\circ F \).
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