You use SAS typically, so there you go. That dude with a SAS webpage, Rick Wicklin (sp?, something like that) released a book totally on simulating data in SAS. I used the Google book sample of it to simulate some basic data last week.
But to be honest if you're doing simulations you're probably going to have to write some code. I'm sure somebody *could* create a stupid GUI to make doing simulations for certain things but it would have the same problem a lot of GUIs have - it's hard to make a menu for every possible option. Code is great because you aren't limited by what is in a menu.
So yeah - you should definitely code your simulations in C. That's the best choice.
noetsi, this is considered by many the 'bible' of SAS simulation for the social sciences. it was written by Xitao Fan (with whom I had a mini-fall out last year during AERA regarding the proper way to simulate multivariate, non-normal data) but the dude knows his stuff and, apparently, his hands-on approach to how to code simulations in SAS makes his book a very good reference:
I think we can boil this down to make life even easier.
Essentially all simulations require random number generation of some sort. We can generate any distribution by transforming uniform random variables. We can generate uniform random variables from an infinite sequence of Bernoulli(.5) random variables. In practice we can just use a finite string of bernoullis. If we have a fair coin we can use that to generate bernoulli(.5) random variables.
Therefore if you want to do a simulation all you really need to do is flip a coin for a long time. This gets rid of all of the coding which I think would make noetsi very happy.
Use @risk. From our discussions and your interest, I don't think you like to do simulation using SAS. Because you need to do some level of programming (If you like proc iml, it may not be that difficult.)
At risk is an addins of excel and mostly gui based. Here is the LINK