Answer:
5
Explanation:
The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean
and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
In this problem, we have that:

On average, how much error would be expected between the sample mean and the population mean?
This is the standard deviation of the sample. We have that
. So

The answer is 5.