CLT Methods

CLT (Central Limit Theorem) Methods refer to statistical techniques that utilize the principle that, when analyzing a large enough sample, the distribution of sample averages tends to be normal (bell-shaped), regardless of the original data distribution. This allows statisticians to make reliable inferences—such as estimating averages or testing hypotheses—even if the underlying data isn’t normally distributed. In practice, CLT methods help simplify complex data analysis by enabling the use of normal distribution tools, improving the accuracy and efficiency of conclusions drawn from sample data.