Question

I’m going to go easy on you for this one! We learned a lot about the t-Test for independent samples, and last week you compared estimated speed (in miles) for smashed into group and hit group. This week, I want you to review that assignment and NOW compute the effect size (Cohen’s D using the pooled variance). To make sure you have all the data you need to calculate the effect size, here are the means and standard deviations for the "hit" and "smashed into" groups from last week.

Group #1: Smashed into mean and SD: Mean = 41.55, Variance = 44.15, SD = 6.64

Group #2: Hit mean and SD:   M = 27.6, Variance = 53.94, SD = 7.34

1. Compute the effect size (Cohen’s d using the pooled variance). Which of the following is the effect size? Round 2 decimal points.
2. What does the pooled Cohen’s d you obtained using the coin study data represent?

3. What is the effect size and why do we report it?

Answer 1

The given information is:

Group 1:

Mean (M1) = 41.55

Variance (s12) = 44.15

Standard deviation (s1) = 6.64

Group 2:

Mean (M2) = 27.6

Variance (s22) = 53.94

Standard deviation (s2) = 7.34

(a):

Compute the effect size (Cohen’s d using the pooled variance) is,

Therefore, the required cohen’d value is 1.9919.

(b).

If cohen’d =0.2, there is small effect.

If cohen’d =0.5, there is medium effect.

If cohen’d =0.8, there is large effect.

In the study, the pooled Cohen’s value represent large effect as its value (1.9919) is greater than 0.8.

(c).

Effect size used to quantify or analyse the amount of association between two independent groups by mainly focussed on the size of differences exists among the two groups. We report the effect size because it will help to explicate the importance of statistical conclusions derived from any research instead of their statistical significance.