False Statements in Reference to Confidence Intervals and Tests of Significance

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More than one of these answers is correct. First, the confidence level is not equal to the significance level. Rather the confidence level is equal to (1 - the significance level). Remember that the significance level of a test is used to quantify the probability of a Type I error, which is defined as the act of incorrectly rejecting the null hypothesis. For example, a confidence level of 95% implies a 5% probability of incorrectly rejecting the null hypothesis (i.e. a Type I error). For example, a hypothesis test associated with a 0.01 significance level indicates a 0.99 level of confidence. The second incorrect statement in this example is that the confidence level of a hypothesis test is found by (1 - alpha), where "alpha" is equal to the probability of a Type I error. Subtracting the probability of a Type II error from one will yield the power of the test. The remaining answers are all correct.