Which statement about Type I errors in hypothesis testing is true?

Which statement about Type I errors in hypothesis testing is true?

• A. The null hypothesis is rejected when the alternative hypothesis is true.
• B. The null hypothesis is not rejected when it is true.
• C. The null hypothesis is rejected when it is true.
• D. The null hypothesis is not rejected when the alternative hypothesis is true.

Answer: (C)

Type I error is the false-positive mistake in hypothesis testing: you conclude there is an effect when none exists. This happens when the null hypothesis is rejected even though it is true. That’s why this statement is the best description. We control how often this occurs with the significance level (alpha), such as 0.05. So, rejecting a true null is the classic Type I error. In contrast, not rejecting a true null is the correct decision, and not rejecting the null when the alternative is true is a Type II error.

Type I error is the false-positive mistake in hypothesis testing: you conclude there is an effect when none exists. This happens when the null hypothesis is rejected even though it is true. That’s why this statement is the best description. We control how often this occurs with the significance level (alpha), such as 0.05. So, rejecting a true null is the classic Type I error. In contrast, not rejecting a true null is the correct decision, and not rejecting the null when the alternative is true is a Type II error.