st230

Which of the following statements about hypothesis tests is TRUE

• The significance level and the probability of Type 1 error are the same

• Power decreases as the sample size increases

• Power corrupts. Statistical power corrupts statistically

There exists a sampling distribution for p-values.

• True

• False

After a regression, we found a p-value of 0.00001 for the slope. What is our conclusion

• There is a significant linear relationship

• There is no correlation

A two-sided test for two proportions was performed at the 5% level, and we got a p-value of 0.0133. What is our conclusion?

• The proportions are different from each other

• The proportions are not different

• The proportions both equal 0

A confidence interval contains every value that would not be rejected by a two-sided hypothesis test

• True for all CIs

• False for all CIs

• True for some CIs, false for others

I calculated the p-value for a t-test, but put n instead of n - 1 for the degrees of freedom. Assuming the critical value doesn't change, what will happen to my p-value?

• Decrease

• Increase

• Stay the same

A p-value is the probability that the null hypothesis is true.

• True

• False

I did a test at the 5% level and got p-value of 0.051. What is my conclusion?

• Reject the null

• Accept the null

• Do not reject the null

In a Chi-Square test, if we assume that the null hypothesis is true, the equation P(A and B) = P(A | B)*P(B) is true. If the null hypothesis is false, then this statement is not generally true.

• True

• False

Suppose the sample size is the same, but we do a better study that results in a lower sample variance. What happens to the power?

• Increase

• Decrease

• No change, since the sample size is the same