Answer:
a. 0.1917
b. 0.0914
d. 0.1580
Step-by-step explanation:
(a)
[tex]P^D = \frac{15}{40} = 0.375[/tex]
[tex]P^E = \frac{11}{60} =0.8133[/tex]
Mean, [tex]\sigma_{P^D-P^E} = P^D-P^E[/tex] = 0.375 -0.1833 = 0.1917
(b) sample prop ? Show your work and label each value.
Mean, = = 0.1917
Standard deviation = [tex]\sqrt{\frac{P^D(1-P^D)}{N_D} +\frac{P^E(1-P^E)}{N_E} }[/tex]
Standard deviation = [tex]\sqrt{\frac{0.375(1-0.375)}{40} +\frac{0.1833(1 - 0.1833)}{60} }[/tex]
Standard deviation = 0.0914
(c)
Normality condition:
np ≥ 10 and n(1-p) ≥ 10
Both the samples satisfy the normality condition.
(d)
The probability is obtained by calculating the z score,
[tex]z = \frac{(P^D-P^E)-(P^d-P^e)}{\sigma_{P^D - P^E}}[/tex]
[tex]z = \frac{0.1917-0.1}{0.0914}[/tex] = 1.0029
P(z > 1.0029) = 1 - P(z ≤ 1.0029)
The probability is obtained from the z distribution table,
P(Z > 1.0029) = 1 - 0.8420 = 0.1580