a. Assume that a 0.01 significance level will be used to test the claim that p 1less thanp 2. Which is better: A hypothesis test or a confidence interval? A hypothesis test is better. b. In general, when dealing with inferences for two population proportions, which two of the following are equivalent: confidence interval method; P-value method; critical value method? ▼ are equivalent, in that they will always lead to the same conclusion. Both of these methods use a standard deviation based on ▼ estimated values of the population proportions, the assumption that the two population proportions are equal, whereas the other method uses a standard deviation based on ▼ estimated values of the population proportions. the assumption that the two population proportions are equal.

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Buttercup

Mathematics

14 April, 15:46

a. Assume that a 0.01 significance level will be used to test the claim that p 1less thanp 2. Which is better: A hypothesis test or a confidence interval? A hypothesis test is better. b. In general, when dealing with inferences for two population proportions, which two of the following are equivalent: confidence interval method; P-value method; critical value method? ▼ are equivalent, in that they will always lead to the same conclusion. Both of these methods use a standard deviation based on ▼ estimated values of the population proportions, the assumption that the two population proportions are equal, whereas the other method uses a standard deviation based on ▼ estimated values of the population proportions. the assumption that the two population proportions are equal.

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Salvatore Copeland · Answer 1

a. A hypothesis test is better

b. confidence interval method; and critical value method will lead to the same conclusion

Step-by-step explanation:

a. A hypothesis test is better

b. confidence interval method; and critical value method will lead to the same conclusion

when samples are taken from a population, the mean values of these samples are approximately normally distributed, that is, the mean values forming the sampling distribution of means is approximately normally distributed. It is also true that if the standard deviations of each of the samples is found, then the standard deviations of all the samples are approximately normally distributed, that is, the standard deviations of the sampling distribution of standard deviations are approximately normally distributed.

Parameters such as the mean or the standard deviation of a sampling distribution are called sampling statistics, S.