What is the primary purpose of a power analysis?

What is the primary purpose of a power analysis?

• A. To decide sampling frame
• B. To estimate data collection time
• C. To estimate the sample size needed to detect an expected effect with a given probability
• D. To assess measurement validity

Answer: (C)

Power analysis is about planning how many participants you need to have a good chance of detecting an effect if there really is one. It asks for the sample size that will give you a specified probability of finding the effect (your study’s power) given an expected effect size and a chosen significance level. In practice, you state how big an effect you care about, the alpha level (how willing you are to risk a false positive), and the desired power (commonly 0.80 or 0.90), and the calculation yields the required sample size. This helps ensure you’re not underpowered (missing real effects) or overpowered (wasting resources). It isn’t about who to include in the study (sampling frame), how long data collection will take, or whether the measurement actually validly captures the concept; it’s about sizing the study to detect effects with a chosen probability.

Power analysis is about planning how many participants you need to have a good chance of detecting an effect if there really is one. It asks for the sample size that will give you a specified probability of finding the effect (your study’s power) given an expected effect size and a chosen significance level. In practice, you state how big an effect you care about, the alpha level (how willing you are to risk a false positive), and the desired power (commonly 0.80 or 0.90), and the calculation yields the required sample size. This helps ensure you’re not underpowered (missing real effects) or overpowered (wasting resources). It isn’t about who to include in the study (sampling frame), how long data collection will take, or whether the measurement actually validly captures the concept; it’s about sizing the study to detect effects with a chosen probability.