Answer: The effect size measures the strength of the relationship between two variables or the difference between two groups.
In the context of a t-test, there are several ways to measure effect size, including n^2 (eta-squared), Cohen's d, omega-squared (ω^2), and the correlation coefficient r.
Of the four options provided, only one includes Cohen's d, which is a commonly used effect size measure for t-tests.
A rule of thumb for interpreting Cohen's d is:
A small effect size is around d = 0.2.
A medium effect size is around d = 0.5.
A large effect size is around d = 0.8 or higher.
Therefore, the only option that identifies a large effect size for a t-test is d = .76.
Explanation: