Answer:
![\mu_(x) = 0.8](https://img.qammunity.org/2021/formulas/mathematics/college/a5vkumw3pahrkkq0gd7btjhaf3dg7fvdla.png)
The shape of this sampling distribution is approximately normal
Explanation:
From the question we are told that
The population proportion is
![p = 0.8](https://img.qammunity.org/2021/formulas/mathematics/college/7r06g7cnzl444m2e5fr2jblvh5iwtrpxxg.png)
The sample size is n = 100
Generally the expected value of this sampling distribution is mathematically represented as
![\mu_(x) = p = 0.8](https://img.qammunity.org/2021/formulas/mathematics/college/feixix8fjjp6y20dfgbo6pyx7jfsq6jhnb.png)
Generally the standard deviation of this sampling distribution is mathematically represented as
![\sigma = \sqrt{ (p(1- p ))/(n ) }](https://img.qammunity.org/2021/formulas/mathematics/college/oqw0f6vf36jltqpbb0ipev8s323z4idfc1.png)
=>
=>
Generally given that the sample is large (i.e n > 30 ) and the standard deviation is finite then the shape of this sampling distribution is approximately normal