Question 880706
1)This problem is an application of a "Sampling Distribution of the Mean" using The Central Limit Theorem.
2)Our population size is 350 and we are sampling 40 members of that population.
3)The central limit theorem states that the sampling distribution of any statistic will be normal or nearly normal, if the sample size is large enough. 
As a rough rule of thumb, many statisticians say that a sample size of 30 is large enough.  Our sample size of 40 is therefore large enough.
The central limit theorem tells us that the mean of the population will be the mean of the sample given that the sample is greater than or equal to 30.
Therefore,
i) sample mean is $50,500.
ii) sample standard deviation is given by the following formula
sample standard deviation = population standard deviation * square root (1/n - 1/N), where n is sample size and N is population size, note that for large populations 1/N approaches 0.
sample standard deviation = 18800 * square root( 1/40 - 1/350) = 2797.529522377 = $2,798.