Which of the following describes the 'power' of a statistical test?
- A The probability of detecting a true effect when it exists (1 − β) ✓
- B The probability of making a Type I error (α)
- C The probability of failing to reject a true null hypothesis
- D The probability of a false positive result
Correct answer: A. The probability of detecting a true effect when it exists (1 − β)
Explanation
Statistical power is defined as 1 − β (where β is the Type II error rate), representing the probability of correctly rejecting a false null hypothesis — i.e., detecting a true effect when it truly exists. Power is typically set at 0.80 (80%) in study design. Higher sample sizes increase power by reducing β.
Reference: Park's Textbook of Preventive and Social Medicine, 27th ed.
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