Probability and sampling distribution examples

The sampling distribution of a statistic is the distribution of all possible values that can be assumed by some statistic, computed from samples of the same size randomly drawn from the same population. 
Construction of sampling distributions :
1.  From a finite population of size N, randomly draw all possible samples of size n. 2.  Compute the statistic of interest for each sample.3.  Create a frequency distribution of the statistic
We are interested in knowing three things about sampling distribution include (the mean, the variance and appearance of the graph (functional form of a sampling distribution).
Distribution of the sample mean. B) Distribution of the difference between two means.
C) Distribution of the sample proportion .D) Distribution of the difference between two proportions
If the cranial length of certain large human
population is normally distributed with a mean
=185.6 mm, and standard deviation=12.7 mm.
what is the probability that a random sample of
size 10 from this population will have a mean
greater than 190 mm? P(z< 1.1) = 0.8643, P(z< -2.99) = 0.0014 , P (z< 2.99)= 0.9986