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.
<span>There are 100 * 99 = 9900 different ways to choose two students out of 100 bandmembers. You and our brother are 2 of that ways: you being selected first and you being selected second. Therefore the probability that you two are selected is 2 / 9900 = 0,000202. You can also think as the probability of you being selected among 100 bandmembers, which is 1/100, times the probability of your brother being selected among 99 members, which is 1/99 => (1/100) * (1/99) = 1/ (100*99) = 1 / 9900; plus the same for your brother being selected first and you second => [1/9900] * 2 = 2/9900, which is the same calculated above.</span>
R would have to be equal to 0.08 in order for it to be true.
Answer:
a
Step-by-step explanation:
Answer:
it is a true
Step-by-step explanation:
because they mean the same thing just written differently