Which factor does NOT directly influence statistical power?

Which factor does NOT directly influence statistical power?

• A. Effect size
• B. Sample size
• C. Number of groups
• D. Variability

Answer: (C)

Power is the probability of correctly rejecting a false null, and it depends most directly on the effect size, the amount of data (sample size), the variability in the data, and the chosen significance level. The number of groups you compare does not by itself set how easy it is to detect a true difference; it can change the analysis structure (like degrees of freedom) and, in practice, how much data you need, but the direct drivers of power are how large the true effect is relative to noise, how much data you collect, and how strict you are about declaring significance.

Power is the probability of correctly rejecting a false null, and it depends most directly on the effect size, the amount of data (sample size), the variability in the data, and the chosen significance level. The number of groups you compare does not by itself set how easy it is to detect a true difference; it can change the analysis structure (like degrees of freedom) and, in practice, how much data you need, but the direct drivers of power are how large the true effect is relative to noise, how much data you collect, and how strict you are about declaring significance.