I am doing a project trying to investigate the effects of various tactics on the outcome of a naval battle from WW1. I have a simulation which runs many simulations of the battle and records statistics such as hits, ships sunk etc. The data is output in frequency density form with a column for each variable that has been recorded and a row for each number 0-20000. For example if I did 100 simulations and 0 ships were sunk in 12 of them then 0.12 would be in the first row of the ships sunk column. I have 10 or so different samples each representing a different naval tactic and each sample is the result of 100,000 simulations.
My question is how do I conduct statistical tests on data of this form and sample size. I simply need to conduct tests to confirm the significance of differences between two samples so I can draw conclusions from them. Some of the data is not normally distributed also. The simulation samples variables relating to the ships in the battle from a distribution each time it runs so each sample can be considered independent.