Calculate Cohen's d for t = 2.12 with N = 25 for each of the two groups.

A) .09
B) .31
C) .61
D) .88

To calculate Cohen's d, we first need to calculate the pooled standard deviation, which is the square root of ([(n1-1) * s1^2 + (n2-1) * s2^2] / [n1 + n2 - 2]) where s1 and s2 are the standard deviations and n1 and n2 are the sample sizes for the two groups.
Assuming equal sample sizes, s1 = s2 and the equation simplifies to s_pooled = s * sqrt(2/(n1+n2)).
With t = 2.12 and N = 25, we can use a t-table to find that the two-tailed p-value is approximately .04. This means we can reject the null hypothesis and conclude that there is a statistically significant difference between the two groups.
Using Cohen's d equation (d = (mean1 - mean2) / s_pooled), we get d = (0 - 2.12) / (s * sqrt(2/50)).
Since we don't have the actual data or standard deviation, we can't calculate d exactly, but we can use approximations. A commonly used approximation is to assume a small effect size is .2, a medium effect size is .5, and a large effect size is .8.
With a calculated d of approximately .61, it falls between a medium and large effect size, so the best choice is C) .61.