Central Limit Theorem Simulation

The Central Limit Theorem Simulation demonstrates that when you repeatedly sample a small part of a population and calculate the average of each sample, these averages tend to form a bell-shaped, normal distribution, regardless of the original population's shape. By simulating this process—drawing many samples and recording their averages—you can observe how the distribution of these averages becomes more predictable and symmetric as the number of samples increases. This helps us understand why many natural and social phenomena tend to follow a normal distribution, enabling better analysis and decision-making based on sample data.