In probability theory, the central limit theorem states that if the population is normally distributed then samples will also be normally distributed for any sample size. But if population is not normal then sample will be normally distributed if sample (of size n) are drawn randomly from a population that has a mean of µ and standard deviation of σ, the sample means are approximately normally distributed for sufficiently large sample size (n ≥ 30).