The **central limit theorem** is one of the most useful concepts in statistics. The theorem is all about drawing samples of a finite size \(n\) from a population. The theorem states that if one collects samples of a large enough sample size \(n\), and calculates each sample’s mean (or sum), the shape of the histogram of those means (or sums) approximates a normal bell shape. The usefulness of the central limit theorem is due to the fact, that **it does not matter what the distribution of the original population is, the distribution of sample means and the sums tend to follow the normal distribution.**