Which statement about statistical power is true?

• A. It is the probability of a Type I error
• B. It is the probability that a study will detect a true effect if it exists
• C. It is the probability that the null hypothesis is true
• D. It is the probability of obtaining a p-value below 0.05 by chance

Answer: (B)

Statistical power is the probability of detecting a true effect if it exists. In other words, it’s 1 minus the probability of a Type II error (failing to reject the null when there is a real effect). Power increases with larger sample size, a larger true effect, less variability, and a higher significance level (though raising alpha trades off with more false positives). This concept isn’t about the chance of a false positive (that’s the Type I error rate, alpha), nor about the null hypothesis being true, nor about the chance of obtaining a p-value below 0.05 under the null. It’s about the study’s ability to reveal a real effect when one is present.