Answer:
Step-by-step explanation:
The sample proportion [tex]\hat p = \dfrac{50}{200}[/tex]
[tex]\hat p = 0.25[/tex]
The null hypothesis and the alternative hypothesis:
[tex]H_o: p = 0.20 \\ \\ H_1 : p > 0.20[/tex]
Thus; the test statistics is:
[tex]Z = \dfrac{\hat p - p_o}{\dfrac{p_o(1-p_o)}{n} }[/tex]
[tex]Z = \dfrac{0.25 -0.20}{\sqrt{\dfrac{0.20(1-0.20)}{200} }}[/tex]
[tex]Z = \dfrac{0.05}{\sqrt{\dfrac{0.16}{200} }}[/tex]
[tex]Z = \dfrac{0.05}{\sqrt{0.0008 }}[/tex]
[tex]Z = 1.768[/tex]
P-value = 2 × P(Z< - 1.768)
From the z tables
P-value = 2 × 0.03853
P-value = 0.07706
Thus, the p-value is 0.05 < P-value < 0.10