Central limit theorem works because if the sample size is sufficiently large, then the theory assumes the majority of the observations from the sample will be

normally distributed and will have a mean that will be approximately equal to the population mean.

Step-by-step explanation: The central limit theorem tries to show that regardless to the variables in a statistical distribution,the sample mean will tend toward approximating the mean of the population for sufficiently large sample size, a sample size or observations that are greater than or equal to 30 is sufficiently large enough.

The theorem helps to understand that as the sample size increases the chances of getting a sample mean that is approximately Equal to the population mean will be high, and the variance will continue to reduce.

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step-by-step explanation: