The law of large numbers in a nut shell means that no matter how many trials I use it wont matter because that can be just a small percentage when compared to something like infinity.
Seams to be the opposite to what Wikipedia says:
In probability theory, the law of large numbers (LLN) is a theorem that describes the result of performing the same experiment a large number of times. According to the law, the average of the results obtained from a large number of trials should be close to the expected value, and will tend to become closer as more trials are performed.
Of course there is a chance to get 75% heads and 25% even with a few million trys but the probability converges to zero.
Also you have to compare the amount of trys to the amount of possible results you can get for one try. Not to infinity.
In less than 10 minutes of coding you could get reference results which would tell you what solution might be the right (if the random-func you use is good).
