Step 1 :Given that the sample size \(n=75\), the population size \(N=20,000\), and the population proportion \(p=0\).
Step 2 :Check the conditions for normality of the sampling distribution of \(\hat{p}\).
Step 3 :The first condition is \(n \leq 0.05N\). Substitute the given values to get \(75 \leq 0.05*20,000 = 1,000\), which is true.
Step 4 :The second condition is \(np(1-p) \geq 10\). Substitute the given values to get \(75*0*(1-0) = 0\), which is not greater than or equal to 10.
Step 5 :Therefore, the shape of the sampling distribution is not normal because both conditions are not satisfied.
Step 6 :The mean of the sampling distribution of \(\hat{p}\) is equal to the population proportion \(p\). In this case, \(p=0\), so \(\mu_{\hat{p}}=0\).
Step 7 :\(\boxed{\text{The shape of the sampling distribution is not normal and the mean is 0.}}\)