What is statistical power defined as in the context of hypothesis testing?
Answer
The probability of correctly rejecting the null hypothesis when it is actually false.
High statistical power means the study has a good chance of detecting a genuine effect if one truly exists.
Related Questions
What does achieving statistical significance indicate at its most basic level?What aspect of a result does statistical significance *not* confirm?What does the alpha level ($\alpha$) commonly set at 0.05 represent?What is the *p*-value mathematically defined as?What fundamental error occurs when researchers conflate statistical significance with what other concept?How is the effect size quantified, and what is its relationship to sample size?What is statistical power defined as in the context of hypothesis testing?If a study with a very large sample size yields a statistically significant result ($p<0.01$) for a small conversion rate increase of $0.001\%$, what is the implication for the finding?What should researchers generally avoid doing when a study fails to achieve statistical significance ($p > 0.05$)?What three distinct assessments must be synthesized for effective interpretation?In fields like medical device safety, how might expert practice often adjust the conventional alpha threshold?