One of the most important theorems in statistical mathematics and probability
theory is the Central Limit Theorem (CLT). It is used almost everywhere where
statistical mathematics is applied. The usefulness of the theorem lies in its simple
definition. The central limit theorem states that if some certain conditions are
satisfied, then the distribution of the arithmetic mean of a number of independent
random variables approaches a normal distribution as the number of variables
approaches infinity. In other words, there is no need to know very much about the
actual distribution of the variables, as long as there are enough instances of them
their sum can be treated as normally distributed. The beauty of the theorem thus
lies in its simplicity. As an example, we show the distribution of the sum of
uniform distributions with 1, 2, 8, and 32 summands respectively in Figure 1.