Asked by
Hawa Zainab Sesay
on Oct 12, 2024Verified
The seller of a loaded die claims that it will favour the outcome 6.We don't believe that claim,and roll the die 350 times to test an appropriate hypothesis.Our P-value turns out to be 0.01.Provide an appropriate conclusion using α = 0.05.
A) We can say there is a 1% chance of not seeing a fair die in the results we observed from natural sampling variation.We conclude the die is loaded.
B) If the die does not favour the outcome 6,then there is only a 1% chance of seeing a sample proportion of the outcome 6 as high (or higher) than that which we observed from natural sampling variation.At α = 0.05,we reject the null hypothesis and conclude that the die will favour the outcome 6.
C) If the die does not favour the outcome 6,then there is only a 1% chance of seeing a sample proportion of the outcome 6 as high (or higher) than that which we observed from natural sampling variation.At α = 0.05,we fail to reject the null hypothesis that the die does not favour the outcome 6.That is,there is insufficient evidence to conclude that the die will favour the outcome 6.
D) There is a 1% chance of a fair die.
E) There is a 99% chance of a fair die.
Loaded Die
A die that has been tampered with to produce a biased outcome, favoring certain numbers over others.
P-Value
The probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true.
Null Hypothesis
A hypothesis used in statistical testing that suggests no significant effect or association between variables, often symbolized as H0.
- Build knowledge and explain the importance of p-values in the context of evaluating hypotheses.
- Learn about the influence of error levels (α) in hypothesis testing on the strategy of decision-making.
- Distinguish between different types of hypothesis tests depending on the scenario.
Verified Answer
KM
Learning Objectives
- Build knowledge and explain the importance of p-values in the context of evaluating hypotheses.
- Learn about the influence of error levels (α) in hypothesis testing on the strategy of decision-making.
- Distinguish between different types of hypothesis tests depending on the scenario.