Simulation can be used to illustrate a number of results from statistics that are difficult to understand with nonsimulation arguments. One is the famous central limit theorem, which says that if you sample enough values from any population distribution and then average these values, the resulting average will be approximately normally distributed. Confirm this by using @RISK with the following population distributions

(run a separate simulation for each):

(a) discrete with possible values 1 and 2 and probabilities 0.2 and 0.8;

(b) exponential with mean 1 (use the RISKEXPON function with the single argument 1);

(c) triangular with minimum, most likely, and maximum values equal to 1, 9, and