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[Objective: Test a Hypothesis for a Population Proportion] Suppose a City

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[Objective: Test a hypothesis for a population proportion] Suppose a city official conducts a hypothesis test to test the claim that the majority of voters support a proposed tax to build sidewalks. Assume that all the conditions for proceeding with a one-sample test on proportions have been met. The calculated test statistic is approximately 1.40 with an associated p-value of approximately 0.081. Choose the conclusion that provides the best interpretation for the p-value at a significance level of [Objective: Test a hypothesis for a population proportion] Suppose a city official conducts a hypothesis test to test the claim that the majority of voters support a proposed tax to build sidewalks. Assume that all the conditions for proceeding with a one-sample test on proportions have been met. The calculated test statistic is approximately 1.40 with an associated p-value of approximately 0.081. Choose the conclusion that provides the best interpretation for the p-value at a significance level of    A)  If the null hypothesis is true, then the probability of getting a test statistic that is as extreme or more extreme than the calculated test statistic of 1.40 is 0.081. This result is surprising and could not easily happen by chance. B)  If the null hypothesis is true, then the probability of getting a test statistic as large or larger than 1.40 is 0.081. This result is not surprising and could easily happen by chance. C)  The p-value should be considered extreme; therefore the hypothesis test proves that the null hypothesis is true. D)  If the null hypothesis is true, then the probability of getting a test statistic that is as extreme or more extreme than the calculated test statistic of 1.40 is 0.081. The result should be doubled for a two-sided test. This result is not surprising and easily happen by chance.


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