It has been usually assumed that a sample data is normally distributed when the sample size is at  least 30. This is the general rule in using central limit theorem based on the sample size being  greater or equal to 30. Many literary works  also  assumed  normality  when  sample  size  is  at  least  30. This  study  aims  to  determine  the least  required sample  size   that  satisfy    normality   assumption  from  three   non-normal  distributions,   Poisson,   Gamma  and  Exponential distributions. Computer simulations are carried out to study the least required sample  size for the three distributions. Through the study, it is found that sample data from Poisson and  Gamma distributions need sample size less than 30, while Exponential needs more than 30 to achieve normality...

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