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Sagot :
To test the hypothesis that the population proportion of people in City A who support increased government spending on education is different from the population proportion in City B, follow these steps:
### Step-by-Step Solution:
1. State the Null and Alternative Hypotheses:
- Null Hypothesis ([tex]\(H_0\)[/tex]): The population proportion of people in City A that support increased government spending on education is equal to the population proportion in City B.
[tex]\[ H_0: p_A = p_B \][/tex]
- Alternative Hypothesis ([tex]\(H_1\)[/tex]): The population proportion of people in City A that support increased government spending is different from the population proportion in City B.
[tex]\[ H_1: p_A \neq p_B \][/tex]
2. Given Values:
- Significance Level ([tex]\(\alpha\)[/tex]): 0.05
- Test Statistic (z): [tex]\(-1.34\)[/tex]
- p-value: 0.180
3. Decision Rule:
- To determine whether to reject or fail to reject the null hypothesis, compare the p-value to the significance level ([tex]\(\alpha = 0.05\)[/tex]).
- If the p-value is less than [tex]\(\alpha\)[/tex], reject the null hypothesis.
- If the p-value is greater than or equal to [tex]\(\alpha\)[/tex], fail to reject the null hypothesis.
4. Comparison with [tex]\(\alpha\)[/tex]:
- p-value (0.180) is greater than [tex]\(\alpha (0.05)\)[/tex].
5. Conclusion Based on p-value:
- Since the p-value is greater than the significance level ([tex]\(\alpha = 0.05\)[/tex]), we fail to reject the null hypothesis.
6. Interpret the Result:
- Failing to reject the null hypothesis means there is not enough evidence to support the claim that the population proportion of people in City A who support increased government spending on education is different from the population proportion in City B.
### Appropriate Conclusions:
- Fail to reject the null hypothesis.
- The conclusion of the hypothesis test is that there is insufficient evidence to support the claim that the population proportion of people in City A that support such spending is different from the population proportion of people in City B.
### Final Answer:
- Fail to reject the null hypothesis.
- The conclusion of the hypothesis test is that there is insufficient evidence to support the claim that the population proportion of people in City A that support such spending is different from the population proportion of people in City B.
### Step-by-Step Solution:
1. State the Null and Alternative Hypotheses:
- Null Hypothesis ([tex]\(H_0\)[/tex]): The population proportion of people in City A that support increased government spending on education is equal to the population proportion in City B.
[tex]\[ H_0: p_A = p_B \][/tex]
- Alternative Hypothesis ([tex]\(H_1\)[/tex]): The population proportion of people in City A that support increased government spending is different from the population proportion in City B.
[tex]\[ H_1: p_A \neq p_B \][/tex]
2. Given Values:
- Significance Level ([tex]\(\alpha\)[/tex]): 0.05
- Test Statistic (z): [tex]\(-1.34\)[/tex]
- p-value: 0.180
3. Decision Rule:
- To determine whether to reject or fail to reject the null hypothesis, compare the p-value to the significance level ([tex]\(\alpha = 0.05\)[/tex]).
- If the p-value is less than [tex]\(\alpha\)[/tex], reject the null hypothesis.
- If the p-value is greater than or equal to [tex]\(\alpha\)[/tex], fail to reject the null hypothesis.
4. Comparison with [tex]\(\alpha\)[/tex]:
- p-value (0.180) is greater than [tex]\(\alpha (0.05)\)[/tex].
5. Conclusion Based on p-value:
- Since the p-value is greater than the significance level ([tex]\(\alpha = 0.05\)[/tex]), we fail to reject the null hypothesis.
6. Interpret the Result:
- Failing to reject the null hypothesis means there is not enough evidence to support the claim that the population proportion of people in City A who support increased government spending on education is different from the population proportion in City B.
### Appropriate Conclusions:
- Fail to reject the null hypothesis.
- The conclusion of the hypothesis test is that there is insufficient evidence to support the claim that the population proportion of people in City A that support such spending is different from the population proportion of people in City B.
### Final Answer:
- Fail to reject the null hypothesis.
- The conclusion of the hypothesis test is that there is insufficient evidence to support the claim that the population proportion of people in City A that support such spending is different from the population proportion of people in City B.
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