The Central Limit Theorem
The theories was introduced by De Moivre and according to it; if we choose a large number of simple random samples, says from any population and find out the mean of each sample, the distribution of these sample means will tend to be described by the common probability distribution along with a mean µ and variance σ^{2}/n. It is true even if the population itself is not normal distribution. Or the sampling distribution of sample means approaches to a normal distribution irrespective of the distribution of population from whereas the sample is consider and approximation to the normal distribution becomes increasingly close along with increase in sample sizes