Question

When sample size increases:____.

A. Standard deviation of the sample mean increases.
B. Confidence interval remains the same.
C. Confidence interval increases.
D. Confidence interval decreases.

Answer 1

D. Confidence interval decreases.

Explanation:

Central Limit Theorem

The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean
`\mu` and standard deviation
`\sigma`, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
`\mu` and standard deviation
`s = (\sigma)/(√(n))`.

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
`\mu = p` and standard deviation
`s = \sqrt{(p(1-p))/(n)}`

When sample size increases:

The standard deviation of the sample mean is:

`s = (\sigma)/(√(n))`

That is, it is inversely proportional to the sample size, so if the sample size incerases, the standard deviation decreases, and so does the confidence interval.

This means that the correct answer is given by option D.