Asked by
Zateeana Nance
on Oct 12, 2024
Verified
The mayor's disapproval rating was previously 13%.After a political ad campaign for a city's mayor,pollsters check the disapproval ratings.They test the hypothesis that the ads produced no change against the alternative that the ratings are now below 13%,and find a P-value of 0.11.Provide an appropriate conclusion using α = 0.10.
A) There is an 89% chance the ads produced no change in ratings.
B) If the ads produced no change in the mayor's disapproval rating,then there is an 11% chance of seeing a sample proportion as low (or lower) than that which we observed from natural sampling variation.At α = 0.10,we reject the null hypothesis and conclude that the disapproval rating is below 13%.
C) There is an 11% chance the ads produced no change in ratings.
D) We can say there is an 11% chance of seeing the ads produce a ratings change in the results we observed from natural sampling variation.We conclude the disapproval ratings are lower.
E) If the ads produced no change in the mayor's disapproval rating,then there is an 11% chance of seeing a sample proportion as low (or lower) than that which we observed from natural sampling variation.At α = 0.10,we fail to reject the null hypothesis that the disapproval rating is 13%.There is insufficient evidence to conclude that the disapproval rating is below 13%.
Disapproval Rating
A metric, often used in politics and public opinion polling, indicating the percentage of respondents who are dissatisfied with a person or policy.
Political Ad
A form of advertising aimed specifically at influencing the decision-making processes of a political landscape, often used during election campaigns.
P-Value
A statistical measure that helps scientists determine the significance of their research results.
- Learn and illustrate the significance of p-values in the scrutiny of hypotheses.
- Understand the significance of α error levels within hypothesis testing and how they affect decision-making strategies.
- Measure the performance of interventions by analyzing hypothesis testing outcomes.
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Learning Objectives
- Learn and illustrate the significance of p-values in the scrutiny of hypotheses.
- Understand the significance of α error levels within hypothesis testing and how they affect decision-making strategies.
- Measure the performance of interventions by analyzing hypothesis testing outcomes.