Consider random samples of size 1200 from a population with proportion 0.65 . Find the standard error of the distribution of sample proportions. Round your answer for the standard error to three decimal places.

Answer:

The standard error of the distribution of sample proportions is of 0.014.

Step-by-step explanation:

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

Consider random samples of size 1200 from a population with proportion 0.65 .

This means that [tex]n = 1200, p = 0.65[/tex]

Find the standard error of the distribution of sample proportions.

Answer:The standard error of the distribution of sample proportions is of 0.014.

Step-by-step explanation:Central Limit TheoremThe Central Limit Theorem establishes that, for a normally distributed random variable X, with mean [tex]\mu[/tex] and standard deviation [tex]\sigma[/tex], the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean [tex]\mu[/tex] and standard deviation [tex]s = \frac{\sigma}{\sqrt{n}}[/tex].

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean [tex]\mu = p[/tex] and standard deviation [tex]s = \sqrt{\frac{p(1-p)}{n}}[/tex]

Consider random samples of size 1200 from a population with proportion 0.65 .This means that [tex]n = 1200, p = 0.65[/tex]

Find the standard error of the distribution of sample proportions.This is s. So

[tex]s = \sqrt{\frac{0.65*0.35}{1200}} = 0.014[/tex]

The standard error of the distribution of sample proportions is of 0.014.