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　　Which of the following statements are not true?
　　I  Type I error occurs when the null hypothesis is not rejected when it is actually false.
　　II Type II error occurs when the null hypothesis is rejected when it is actually true.
　　IIIType I error occurs when the alternate hypothesis is wrongly accepted.
　　IV Minimizing the probability of Type II error maximizes the power of the test.
　　A  I and II
　　B  I and III
　　C  II and IV
　　D  I, II and IV
　　答案：A
　　答案解析：
　　Explanation: In hypothesis testing we accept the alternate hypothesis if the null hypothesis has been rejected. Type I error happens if the null hypothesis is rejected when it is actually true. Type II error happens if the null hypothesis is accepted when it is actually false. The power of the test is the probability of correctly rejecting the null hypothesis (when it is false), so minimizing Type II errors would maximize the power of the test.
　　相关知识点：Type I and Type II Errors
　　Type I error:
　　l  Rejection of the null hypothesis when it is actually true.
　　l  The significance level is the probability of making a Type I error.
　　Type II error:
　　l  Failure to reject the null hypothesis when it is actually false.
　　l  The probability that the test correctly rejects the null hypothesis when the alternative is true is the power of the test. It is just one minus the probability of a Type II error.
　　本期试题：
　　An analyst is conducting a two-tailed z-test to determine if small cap returns are significantly different from 10%. The sample size is 200 and the computed z-statistic is 2.3. Using a 5% level of significance, which of the following statements is most accurate?
　　A  Reject the null hypothesis and conclude that small cap returns are not significantly different from 10%.
　　B  Fail to reject the null hypothesis and conclude that small cap returns are significantly different from 10%.
　　C  Fail to reject the null hypothesis and conclude that small cap returns are close enough to 10% that we cannot say they are significantly different from 10%.
　　D  Reject the null hypothesis and conclude that small cap returns are significantly different from 10%.
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