Question:

If true explain and if false give an example.

1. The significance level of a statistical test is equal to the probability that the null hypothesis is true.
2. If the significance level of a test is decreased, the power of the test would be expected to increase.
3. The probability that the null hypothesis is falsely rejected is equal to the power of the test.
4. A Type I error is more serious than a Type II error.
5. If a Type I error occurs then the test statistics falls in the rejection region of the test.
6. The power of a test is determined by the null distribution of the test statistic.

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