Final answer:
A Type I error occurs when the null hypothesis is rejected, even though it is actually true. On the other hand, a Type II error occurs when the null hypothesis is not rejected, even though it is actually false. The correct answer is A.
Step-by-step explanation:
A Type I error occurs when the null hypothesis is rejected, even though it is actually true. This is also known as a false positive. On the other hand, a Type II error occurs when the null hypothesis is not rejected, even though it is actually false. This is also known as a false negative.
The correct answer is A. Type I; Type II. A Type I error is incorrectly rejecting a true null hypothesis, and a Type II error is incorrectly accepting or failing to reject a false null hypothesis.
Rejecting H0 when it is true is called a Type I error, and failing to reject H0 when it is false is called a Type II error. Therefore, the correct answer to the question is A. Type I; Type II. A Type I error occurs when a true null hypothesis is incorrectly rejected, and a Type II error occurs when a false null hypothesis is incorrectly accepted or not rejected.
The probabilities of these errors are denoted by the Greek letters alpha (a) for a Type I error, and beta (B) for a Type II error. The power of the test, 1 – B, quantifies the likelihood that a test will yield the correct result of a true alternative hypothesis being accepted, with a high power being desirable.