Let p be the population proportion .
Then, [tex]p=\dfrac{5000}{20000}=0.25[/tex]
According to the given information, we have
[tex]a)\ \text{Null hypothesis }H_0: p=0.25\\\\b)\ \text{Alternative hypothesis} H_a: p\neq0.25[/tex], since alternative hypothesis is two-tailed , so the hypothesis test is a two-tail test.
Since sample size is large (n> 30), we use z-test.
Let us consider 95% confidence i.e.[tex]\alpha=0.05[/tex].
c) Critical value = [tex]z_{\alpha/2}=\pm1.96[/tex]
Sample proportion : [tex]\hat{p}=\dfrac{96}{300}=0.32[/tex]
d) Test statistic : [tex]z=\dfrac{\hat{p}-p}{\sqrt{\dfrac{p(1-p)}{n}}}[/tex]
i.e. [tex]z=\dfrac{0.32-0.25}{\sqrt{\dfrac{0.25(0.75)}{300}}}=2.8[/tex]
e) P-value (for two-tail) : [tex]2(Pz>2.8)=0.0051103[/tex]
f) P-value is the probability value that we have falsely rejected the null hypothesis.
g) Since observed z-value (2.8) does not lie in critical interval (-1.96, 1.96), it means the null hypothesis is rejected.