Which statement describes a Type I error?

• A. Rejecting a true null hypothesis (false positive).
• B. Failing to reject a true null hypothesis.
• C. Rejecting a false null hypothesis.
• D. Failing to reject a false null hypothesis.

Answer: (A)

Type I error is when you reject a true null hypothesis. In practical terms, it’s a false positive: you conclude there is an effect or difference when there really isn’t. The chance of making this error is set by the significance level, alpha. The other scenarios describe different outcomes: failing to reject a true null is a correct decision; rejecting a false null is a true finding (the study detects an actual effect); failing to reject a false null is a Type II error (missing a real effect).