What is the purpose of a power analysis?

• A. To determine the sample size needed to detect a given effect with desired power.
• B. To compute the p-value after data collection.
• C. To adjust the observed effect size.
• D. To measure the reliability of a test.

Answer: (A)

Power analysis helps researchers plan how many participants are needed to reliably detect an effect of a given size at a chosen significance level with a specified probability of finding it if it truly exists. It combines the expected effect size, the alpha level, and the desired power (often 0.8). If the expected effect is small, you’ll need a larger sample; bigger effects require fewer participants. This planning step helps avoid underpowered studies that might miss real effects and ensures resources are used efficiently. It isn’t about computing p-values after data collection, adjusting observed effect sizes, or measuring the reliability of a test.