The Central limit theorem shows how the mean of a sample distribution approaches the normal distribution when the size of the sample gets larger. In this method, random samples of the population are chosen from a large population and the mean is estimated.
This helps in estimating the mean of a large population without actually calculating the mean of the whole population. If there is an increase in the sample size, a bell-shaped curve is approximated by the frequency distribution.