If other factors are held constant,how does sample size influence the likelihood of rejecting the null hypothesis and measures of effect size such as r² and Cohen's d? A)A larger sample increases both the likelihood and measures of effect size. B)A larger sample increases the likelihood but has little influence on measures of effect size. C)A larger sample decreases the likelihood but has little influence on measures of effect size. D)A larger sample decreases both the likelihood and measures of effect size.

Question

Quizplus · Accepted Answer

A larger sample size increases the power of the test, which means it increases the likelihood of rejecting the null hypothesis. However, the measures of effect size such as r² and Cohen's d are not affected by sample size as they are standardized measures that are independent of the sample size. Thus, the correct answer is B that the larger sample size increases the likelihood but has little influence on measures of effect size.

If Other Factors Are Held Constant,how Does Sample Size Influence