Which factor does not directly influence statistical power?

• A. The color of the testing room.
• B. Alpha level.
• C. Effect size.
• D. Sample size.

Answer: (A)

Statistical power is the probability of detecting a true effect when one exists. It hinges on factors that directly affect how clearly the data reveal the effect: the alpha level you set for significance, the size of the actual effect, and how much data you collect (sample size). The color of the testing room doesn’t enter the power calculation or change the underlying signal versus noise in the way those factors do. It might influence participant comfort or mood in an indirect way, but it’s not a direct lever in determining the likelihood of detecting an effect.

In contrast, increasing the alpha level makes it easier to declare significance, which raises power. A larger true effect is inherently easier to detect, boosting power as well. Collecting more data reduces variability and strengthens the signal, also increasing power.