CLT (Central Limit Theorem)

The Central Limit Theorem (CLT) is a fundamental concept in statistics that states that when you take a large enough sample from any population, the average of the sample will tend to be close to the average of the entire population, regardless of the population's distribution. As you increase the sample size, the distribution of those sample averages will form a normal distribution (bell curve), even if the original data is not normally distributed. This principle allows statisticians to make inferences about populations based on sample data, making it essential for research and data analysis.