When you take samples from a population and compute a proportion from each one, you can consider the distribution of those proportions. This is called the sampling distribution for the population proportion. The Central Limit Theorem tells us that the sampling distribution for the population proportion is

Step-by-step explanation:

This is a fill in the gap question:

The Central Limit Theorem tells us that the sampling distribution for the population proportion is approximately normal with the population proportion as its mean. The theorem of the central limit is a set of results on the weak convergence of a series of random variables in probability. Intuitively, according to these results, any sum of independent and identically distributed random variables tends towards a certain random variable.

Similarly; from the question:

The mean of the sampling distribution is given by

Suppose p is the population proportion and let say n is the sample size; then :

The standard deviation of the sampling distribution can be represented by :

x² + 3x + 7 = 0       [ax² + bx + c]

a = 1

b = 3

c = 7

quadratic formula:

    (+/- is this ±)

plug in the numbers into the variables

your answer is a

x = 3 ± √(5+y)