Mini toolsDefinition
A principle stating that as the number of trials increases, the average of results tends to converge to the expected value.
Detailed Explanation
The Law of Large Numbers states that the sample average converges to the true population mean as sample size increases. It comes in two forms: weak (convergence in probability) and strong (almost sure convergence). This principle underlies many statistical methods and provides theoretical justification for empirical probability estimates.
Use Cases
Monte Carlo simulations, statistical quality control, experimental design, machine learning validation, and risk assessment.
