What does a p-value from a statistical hypothesis test quantify?

a. The probability that the null hypothesis is not true.

b. The probability that the null hypothesis is true.

c. The probability of getting a sample estimate as or more extreme (as "far" or "farther" from the null value) if the null hypothesis is true.

d. The probability of getting a sample estimate as or more extreme (as "far" or "farther" from the null value) if the alternative hypothesis is true.

e. The probability that the study is valid.

2.

Generally speaking, what is the null hypothesis for a comparison of a population level quantity (parameter) between two populations.

a. The two underlying populations being compared have different values of the parameter.

b. The two samples being compared have different values of the parameter.

c. The two underlying populations being compared have the same values of the parameter.

d. The two samples being compared have the same values of the parameter.

3.

Suppose you perform a paired sample t-test to compare the mean difference in blood pressure before and after an intervention. The resulting p-value is 0.001. What can you say about the 95% confidence interval for the mean difference in blood pressure after the intervention compared to before the intervention?

a. The 95% CI will include 1.

b. The 95% CI will include 0.

c. The 95% CI will not include 1.

d. The 95% CI will not include 0.

4.

What is the primary difference between the paired t-test and the two-sample t-test?

a. The null hypotheses are difference for these two tests.

b. The standard error computations for the sample mean difference are different for these two tests.

c. These tests are conceptually completely different.

d. The alpha level is generally higher for two-sample t-tests.

5.

When a researcher specifies an alpha level of 0.05 for a two-sample t-test, what does this mean?

a. The chances that the study results are important is greater than 0.05.

b. The chances of rejecting the null hypothesis when the null hypothesis is true is 0.05.

c. THe chances of rejecting the null hypothesis when the alternative hypothesis is true is 0.05.

d. The p-value will be equal to 0.05.

6.

When a p-value is above the chosen alpha-level (rejection level) for a test, why is the decision to "fail to reject the null" and not "accept the null as the truth"?

a. Because double negatives make the world go around.

b. Because the reasons for not rejecting the null are not always apparent, especially with smaller samples.

7.

Suppose you wish to perform a two-sample t-test to compare the mean of a continuous outcome between two populations based on the results from two samples. Which of the following test related quantity does not depend on the data from these samples?

a. The mean difference between the two samples

b. The estimated standard error of the mean difference between the two samples

c. The alpha level of the test

d. The endpoint of the corresponding 95% CI for the population level mean difference

8.

Suppose a researcher performs the appropriate hypothesis test for the population measure being compared between two populations. His resulting p-vaue is 0.023. Assuming an alpha-level of 0.05, what decision should he make?

a. Reject the null hypothesis in favor of the alternative hypothesis.

b. Reject the alternative hypothesis in favor of the null hypothesis

c. Fail to reject the null hypothesis

d. Fail to reject the alternative hypothesis