Law of Large Numbers

The Law of Large Numbers is a statistical principle stating that as the size of a sample increases, its average will get closer to the expected value or true average of the entire population. For example, if you flip a coin many times, the proportion of heads and tails will approach 50% as you increase the number of flips. Essentially, it suggests that larger samples give more reliable and accurate results, reducing the impact of random variation. Thus, in many cases, the more observations you make, the more certain you become about the overall outcome.