The law of large numbers just tells us that my sample mean will approach my expected value of the random variable. Or I could also write it as my sample mean will approach my population mean for n approaching infinity. And I'll be a little informal with what is approach or what is convergence mean, but I think you have the general intuitive sense that if I take a large enough sample here, that I'm going to end up getting the expected value of the population as a whole. And I think to a lot of us that's kind of intuitive, that if I do enough trials that over large samples, that the trials would kind of give me the numbers that I would expect given the expected value and the probability of all that. But I think it's often a little bit misunderstood in terms of why that happens. And before I go into that, let me give you a particular example. So the law of large numbers will just tell us that, let's say I have a random variable x is equal to the number of heads after 100 tosses of a fair coin.