Answer:
Step-by-step explanation:
a) The formula for determining the standard error of the distribution of differences in sample proportions is expressed as
Standard error = √{(p1 - p2)/[(p1(1 - p1)/n1) + p2(1 - p2)/n2}
where
p1 = sample proportion of population 1
p2 = sample proportion of population 2
n1 = number of samples in population 1,
n2 = number of samples in population 2,
From the information given
p1 = 0.77
1 - p1 = 1 - 0.77 = 0.23
n1 = 58
p2 = 0.67
1 - p2 = 1 - 0.67 = 0.33
n2 = 70
Standard error = √{(0.77 - 0.67)/[(0.77)(0.23)/58) + (0.67)(0.33)/70}
= √0.1/(0.0031 + 0.0032)
= √1/0.0063
= 12.6
the standard error of the distribution of differences in sample proportions is 12.6
b) the sample sizes are large enough for the Central Limit Theorem to apply because it is greater than 30
