Statistics: Laws of Large Numbers

This lecture covers fundamental theorems in statistics, including the strong and weak laws of large numbers. It explains how random variables converge to their expectations as the sample size increases. The central limit theorem is also discussed, showing how sums of independent random variables tend towards a normal distribution. Practical applications and limitations of these theorems are illustrated, emphasizing the importance of appropriate probability models for accurate data description.