Which of the following statements about hypothesis testing is most accurate?
　　A. The probability of a Type I error is equal to the significance level of the test.
　　B. If you can disprove the null hypothesis, then you have proven the alternative hypothesis.
　　C. To test the claim that X is greater than zero, the null hypothesis would be H0: X > 0.
　　D. The power of a test is one minus the probability of a Type I error.
　　Answer:A
　　The probability of getting a test statistic outside the critical value(s) when the null is true is the level of significance and is the probability of a Type I error. The power of a test is 1 minus the probability of a Type II error. Hypothesis testing does not prove a hypothesis, we either reject the null or fail to reject it. The appropriate null would be "X ≤ 0" with "X > 0" as the alternative hypothesis.