Answer:

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:

Solution to the problem
And for this case we can assume:
the mean for females
the mean for males
represent the deviations for both groups
And if we replace we got:

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:
a. The mean can be found using the AVERAGE() function.
x = 272.7
b. The standard deviation can be found with the STDEV() function.
s = 39.9
c. The t-score can be found with the T.INV.2T() function. The confidence level is 0.04, and the degrees of freedom is 26.
t = 2.162
d. Find the lower and upper ends of the confidence interval.
Lower = 272.7 − 2.162 × 39.9 = 186.5
Upper = 272.7 + 2.162 × 39.9 = 358.9
Answer:
x = 20
Step-by-step explanation: