CLT Principles

The Central Limit Theorem (CLT) states that when you take many independent samples from any population, regardless of its original distribution, and calculate their averages, those averages will tend to form a normal (bell-shaped) distribution. This means that even if the data is skewed or irregular, the distribution of sample means will approximate a normal curve if the sample size is large enough. The CLT underpins many statistical methods, allowing us to make inferences about large groups based on smaller samples with confidence about their overall characteristics.