What does a power analysis determine?

A power analysis is primarily used to determine the probability of correctly rejecting the null hypothesis when it is false, depending on factors such as sample size, effect size, and significance level. It helps researchers understand how likely they are to detect an effect if one truly exists. A higher power means there is a greater chance of detecting an effect, while a lower power indicates a risk of missing it. This aspect is crucial for planning research studies, as it informs decisions about sample size and helps to ensure adequate power to detect meaningful effects.

In contrast, determining the level of significance needed for a study focuses on setting cutoff criteria for evaluating results, while selecting the best statistical test relates to the nature of the data and research questions. Assessing potential bias in research design is also a critical consideration but is unrelated to the concept of power analysis. Thus, option B encapsulates the primary role of power analysis in statistical methodologies.