CEVAP:

Central limit theorem is one of the most important theorems in statistics. If you take independent samples one by one from a population with a known arithmetic mean and standard deviation and calculate the means of these samples, central limit theorem states that the shape of the distribution of the sample means will be approximately Normal distribution. Central Limit Theorem also indicates that without the regard of the shape of a population parameter’s distribution (symmetric, asymmetric, left skewed or right skewed), the sampling distribution of the sample mean approximates to the normal distribution as the sample size increases.