The larger the effect size, the greater the likelihood
A) of ignoring the null hypothesis
B) of rejecting the null hypothesis
C) of committing the Type 2 error
D) that the population means are not significantly different

Question

Quizplus · Accepted Answer

An effect size is a measure of the strength of the relationship between the independent and dependent variables in a study. A larger effect size indicates a stronger relationship between the variables, and thus a greater likelihood of rejecting the null hypothesis (i.e. that there is no significant difference between the population means). Therefore, option B is the correct answer.

The Larger the Effect Size, the Greater the Likelihood