All else being equal, which of the following methods can help increase the power of a study?

• A. Decreasing the effect size
• B. Increasing the population variance
• C. Increasing the sample size
• D. Using a higher significance level (for example, $\alpha$ = $0.10$ instead of $0.05$)

Answer: (C)

Verified step by step guidance

1. Understand that the power of a study is the probability of correctly rejecting the null hypothesis when it is false. Power depends on several factors: effect size, sample size, population variance, and significance level (\alpha).
2. Recognize that decreasing the effect size actually reduces power because smaller effects are harder to detect.
3. Note that increasing the population variance increases the noise in the data, which makes it harder to detect an effect, thus decreasing power.
4. Increasing the sample size reduces the standard error, making it easier to detect an effect and therefore increases the power of the study.
5. Using a higher significance level (e.g., \alpha = 0.10 instead of 0.05) increases power because it makes it easier to reject the null hypothesis, but it also increases the risk of a Type I error.