The Law of Large Numbers (LLN) is a fundamental concept in probability and statistics. It states that as the size of a sample increases, the sample mean (average) will get closer and closer to the expected value (true mean) of the population from which the sample is drawn. In other words:If you repeat an experiment a large number of times, the average result will likely be close to the theoretical average. For example, if you flip a fair coin many times, the proportion of heads will get closer to 50% as the number of flips increases. Key Points: Sample Mean Approaches Population Mean: With more data, averages stabilize. Two Types: Weak Law of Large Numbers: Convergence in probability. Strong Law of Large Numbers: Almost sure convergence. Applications: Gambling, insurance, polling, quality control, and more. Edit By: Dr. Engineer / Adel Ramadan