Answer:
For this case we select a sample size of n from a large population (n>30) and we know the following properties for the random variable X:

From the central limit theorem we know that the distribution for the sample mean
is given by:
The sampling distribution of x overbar has mean
and standard deviation
.
Explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
Solution to the problem
For this case we select a sample size of n from a large population (n>30) and we know the following properties for the random variable X:

From the central limit theorem we know that the distribution for the sample mean
is given by:
The sampling distribution of x overbar has mean
and standard deviation
.