Question

A researcher working in a Human Resources department was interested in gender and sales figures so he conducted a t-test. The mean for males was 66.25 and the mean for females was 78.24, with both groups having a standard deviation of 7. What is the effect size using Cohen’s d?

Answer 1

Answer:

$d = \frac{78.24 -66.25}{\sqrt{\frac{7^2 +7^2}{2}}}= 1.713$

For the interpretation we consider a value for d small is is between 0-0.2, medium if is between 0.2-0.8 and large if is higher than 0.8.

And on this case 1.713>0.8 so we have a large effect size

This value of d=1.713 are telling to us that the two groups differ by 1.713 standard deviation and we will have a significant difference between the two means.

Step-by-step explanation:

Previous concepts

The Effect size is a "quantitative measure of the magnitude of the experimenter effect. "

The Cohen's d effect size is given by  the following formula:

$d = \frac{\bar X_1 -\bar X_2}{\sqrt{\frac{s^2_1 +s^2_2}{2}}}$

Solution to the problem

And for this case we can assume:

$\bar X_1 =78.24$ the mean for females

$\bar X_2 =66.25$ the mean for males

$s_1 = s_2= 7$ represent the deviations for both groups

And if we replace we got:

$d = \frac{78.24 -66.25}{\sqrt{\frac{7^2 +7^2}{2}}}= 1.713$

For the interpretation we consider a value for d small is is between 0-0.2, medium if is between 0.2-0.8 and large if is higher than 0.8.

And on this case 1.713>0.8 so we have a large effect size

This value of d=1.713 are telling to us that the two groups differ by 1.713 standard deviation and we will have a significant difference between the two means.