What is the correct description of Type I and Type II errors in hypothesis testing?

What is the correct description of Type I and Type II errors in hypothesis testing?

• A. Type I error is a false negative; Type II error is a false positive.
• B. Type I error is false positive; Type II error is false negative.
• C. Type I error is a correct rejection of the null.
• D. Type II error is a correct failure to reject the null.

Answer: (B)

In hypothesis testing, you decide whether to reject the null hypothesis. A Type I error happens when you reject the null even though it’s true, which is a false positive. A Type II error happens when you fail to reject the null even though it’s false, which is a false negative. So the correct description assigns Type I to false positives and Type II to false negatives, matching the standard definitions. The other statements mix up these ideas or describe correct decisions as errors, so they don’t fit the standard terminology.

In hypothesis testing, you decide whether to reject the null hypothesis. A Type I error happens when you reject the null even though it’s true, which is a false positive. A Type II error happens when you fail to reject the null even though it’s false, which is a false negative. So the correct description assigns Type I to false positives and Type II to false negatives, matching the standard definitions. The other statements mix up these ideas or describe correct decisions as errors, so they don’t fit the standard terminology.