Question

An independent-measures study with n=8 in each treatment produces M=96 for the first treatment and M=91 for the second treatment with a pooled variance of 25 . What is Cohen's d for these data?

Answer 1

Cohen's d for the provided data is 1.0, which is considered a large effect size according to Cohen's standards, indicating a substantial difference between the two treatments.

Step-by-step explanation:

The student is asking about calculating Cohen's d, which is the measure of effect size for the difference between two means. Cohen's d is found by subtracting the second mean (M2) from the first mean (M1) and dividing the result by the pooled standard deviation (Spooled). In this case, the means are M1=96 and M2=91, and the pooled variance is 25 (which means Spooled is the square root of the variance, so Spooled=5). The formula for Cohen's d is d = \((M1 - M2) / Spooled\).

Let's calculate Cohen's d for these data:

d = (96 - 91) / 5 = 5 / 5 = 1.0

According to Cohen's standards, an effect size of 1.0 is considered a large effect size, as it exceeds the threshold of 0.8 for large effect sizes. This implies that the difference between the two treatments is substantial and likely to be of practical significance.