A Type II (beta) error in hypothesis testing refers to:
- A Rejecting a true null hypothesis
- B Failing to reject a false null hypothesis ✓
- C Accepting a true null hypothesis
- D Detecting an effect that does not exist
Correct answer: B. Failing to reject a false null hypothesis
Explanation
A Type II (beta) error occurs when a false null hypothesis is not rejected — i.e., failing to detect a real effect. Its probability is denoted beta (β), and the power of a study = 1 – β. Type I (alpha) error is the converse: rejecting a true null hypothesis, creating a false positive.
Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.
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